{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e9f7603f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import tushare as ts\n",
    "import re\n",
    "import os\n",
    "import time\n",
    "from sqlalchemy import text,create_engine\n",
    "from funcs import *\n",
    "from tqdm.notebook import tqdm\n",
    "from loguru import logger\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "token = '1501ffe708345cffa38d9bbc0bd371e93b4b7412e7a8e1f811d3c442'\n",
    "ts.set_token(token)\n",
    "pro = ts.pro_api(token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "89b7faf8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df_所有合约 = get_所有期货合约信息()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "aa36d8bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>symbol</th>\n",
       "      <th>exchange</th>\n",
       "      <th>name</th>\n",
       "      <th>fut_code</th>\n",
       "      <th>multiplier</th>\n",
       "      <th>trade_unit</th>\n",
       "      <th>per_unit</th>\n",
       "      <th>quote_unit</th>\n",
       "      <th>quote_unit_desc</th>\n",
       "      <th>d_mode_desc</th>\n",
       "      <th>list_date</th>\n",
       "      <th>delist_date</th>\n",
       "      <th>d_month</th>\n",
       "      <th>last_ddate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5562</th>\n",
       "      <td>RB0909.SHF</td>\n",
       "      <td>RB0909</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢0909</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2009-03-27</td>\n",
       "      <td>2009-09-15</td>\n",
       "      <td>200909</td>\n",
       "      <td>20090922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5563</th>\n",
       "      <td>RB0910.SHF</td>\n",
       "      <td>RB0910</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢0910</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2009-03-27</td>\n",
       "      <td>2009-10-15</td>\n",
       "      <td>200910</td>\n",
       "      <td>20091022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5564</th>\n",
       "      <td>RB0911.SHF</td>\n",
       "      <td>RB0911</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢0911</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2009-03-27</td>\n",
       "      <td>2009-11-16</td>\n",
       "      <td>200911</td>\n",
       "      <td>20091123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5565</th>\n",
       "      <td>RB0912.SHF</td>\n",
       "      <td>RB0912</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢0912</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2009-03-27</td>\n",
       "      <td>2009-12-15</td>\n",
       "      <td>200912</td>\n",
       "      <td>20091222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5566</th>\n",
       "      <td>RB1001.SHF</td>\n",
       "      <td>RB1001</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢1001</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2009-03-27</td>\n",
       "      <td>2010-01-15</td>\n",
       "      <td>201001</td>\n",
       "      <td>20100122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5743</th>\n",
       "      <td>RB2410.SHF</td>\n",
       "      <td>RB2410</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢2410</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2023-10-17</td>\n",
       "      <td>2024-10-15</td>\n",
       "      <td>202410</td>\n",
       "      <td>20241017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5744</th>\n",
       "      <td>RB2411.SHF</td>\n",
       "      <td>RB2411</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢2411</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2023-11-16</td>\n",
       "      <td>2024-11-15</td>\n",
       "      <td>202411</td>\n",
       "      <td>20241119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5745</th>\n",
       "      <td>RB2412.SHF</td>\n",
       "      <td>RB2412</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢2412</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2023-12-18</td>\n",
       "      <td>2024-12-16</td>\n",
       "      <td>202412</td>\n",
       "      <td>20241218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5746</th>\n",
       "      <td>RB2501.SHF</td>\n",
       "      <td>RB2501</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢2501</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2024-01-16</td>\n",
       "      <td>2025-01-15</td>\n",
       "      <td>202501</td>\n",
       "      <td>20250117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5747</th>\n",
       "      <td>RB2502.SHF</td>\n",
       "      <td>RB2502</td>\n",
       "      <td>SHFE</td>\n",
       "      <td>螺纹钢2502</td>\n",
       "      <td>RB</td>\n",
       "      <td>None</td>\n",
       "      <td>吨</td>\n",
       "      <td>10.0</td>\n",
       "      <td>人民币元/吨</td>\n",
       "      <td>1人民币元/吨</td>\n",
       "      <td>实物交割</td>\n",
       "      <td>2024-02-20</td>\n",
       "      <td>2025-02-17</td>\n",
       "      <td>202502</td>\n",
       "      <td>20250219</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>186 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         ts_code  symbol exchange     name fut_code multiplier trade_unit  \\\n",
       "5562  RB0909.SHF  RB0909     SHFE  螺纹钢0909       RB       None          吨   \n",
       "5563  RB0910.SHF  RB0910     SHFE  螺纹钢0910       RB       None          吨   \n",
       "5564  RB0911.SHF  RB0911     SHFE  螺纹钢0911       RB       None          吨   \n",
       "5565  RB0912.SHF  RB0912     SHFE  螺纹钢0912       RB       None          吨   \n",
       "5566  RB1001.SHF  RB1001     SHFE  螺纹钢1001       RB       None          吨   \n",
       "...          ...     ...      ...      ...      ...        ...        ...   \n",
       "5743  RB2410.SHF  RB2410     SHFE  螺纹钢2410       RB       None          吨   \n",
       "5744  RB2411.SHF  RB2411     SHFE  螺纹钢2411       RB       None          吨   \n",
       "5745  RB2412.SHF  RB2412     SHFE  螺纹钢2412       RB       None          吨   \n",
       "5746  RB2501.SHF  RB2501     SHFE  螺纹钢2501       RB       None          吨   \n",
       "5747  RB2502.SHF  RB2502     SHFE  螺纹钢2502       RB       None          吨   \n",
       "\n",
       "      per_unit quote_unit quote_unit_desc d_mode_desc  list_date delist_date  \\\n",
       "5562      10.0     人民币元/吨         1人民币元/吨        实物交割 2009-03-27  2009-09-15   \n",
       "5563      10.0     人民币元/吨         1人民币元/吨        实物交割 2009-03-27  2009-10-15   \n",
       "5564      10.0     人民币元/吨         1人民币元/吨        实物交割 2009-03-27  2009-11-16   \n",
       "5565      10.0     人民币元/吨         1人民币元/吨        实物交割 2009-03-27  2009-12-15   \n",
       "5566      10.0     人民币元/吨         1人民币元/吨        实物交割 2009-03-27  2010-01-15   \n",
       "...        ...        ...             ...         ...        ...         ...   \n",
       "5743      10.0     人民币元/吨         1人民币元/吨        实物交割 2023-10-17  2024-10-15   \n",
       "5744      10.0     人民币元/吨         1人民币元/吨        实物交割 2023-11-16  2024-11-15   \n",
       "5745      10.0     人民币元/吨         1人民币元/吨        实物交割 2023-12-18  2024-12-16   \n",
       "5746      10.0     人民币元/吨         1人民币元/吨        实物交割 2024-01-16  2025-01-15   \n",
       "5747      10.0     人民币元/吨         1人民币元/吨        实物交割 2024-02-20  2025-02-17   \n",
       "\n",
       "     d_month last_ddate  \n",
       "5562  200909   20090922  \n",
       "5563  200910   20091022  \n",
       "5564  200911   20091123  \n",
       "5565  200912   20091222  \n",
       "5566  201001   20100122  \n",
       "...      ...        ...  \n",
       "5743  202410   20241017  \n",
       "5744  202411   20241119  \n",
       "5745  202412   20241218  \n",
       "5746  202501   20250117  \n",
       "5747  202502   20250219  \n",
       "\n",
       "[186 rows x 15 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_所有合约[df_所有合约['fut_code']=='RB']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd816e27",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "35f16dcf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SHFE', 'DCE', 'CZCE', 'CFFEX', 'INE', 'GFEX']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exchanges = df_所有合约['exchange'].value_counts().keys().tolist()\n",
    "exchanges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6105600d",
   "metadata": {},
   "outputs": [],
   "source": [
    "exchange_dict = {}\n",
    "for exchange in exchanges:\n",
    "    exchange_dict.update({\n",
    "        exchange:df_所有合约[df_所有合约['exchange']==exchange]['fut_code'].value_counts().keys().tolist()})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "be13002c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'SHFE': ['AL',\n",
       "  'CU',\n",
       "  'RU',\n",
       "  'FU',\n",
       "  'ZN',\n",
       "  'AU',\n",
       "  'WR',\n",
       "  'RB',\n",
       "  'PB',\n",
       "  'AG',\n",
       "  'BU',\n",
       "  'HC',\n",
       "  'SN',\n",
       "  'NI',\n",
       "  'SP',\n",
       "  'SS',\n",
       "  'AO',\n",
       "  'BR'],\n",
       " 'DCE': ['L',\n",
       "  'P',\n",
       "  'V',\n",
       "  'M',\n",
       "  'J',\n",
       "  'B',\n",
       "  'Y',\n",
       "  'A',\n",
       "  'JM',\n",
       "  'I',\n",
       "  'FB',\n",
       "  'BB',\n",
       "  'PP',\n",
       "  'JD',\n",
       "  'C',\n",
       "  'EG',\n",
       "  'RR',\n",
       "  'CS',\n",
       "  'EB',\n",
       "  'PG',\n",
       "  'LH'],\n",
       " 'CZCE': ['TA',\n",
       "  'FG',\n",
       "  'CF',\n",
       "  'SM',\n",
       "  'SF',\n",
       "  'MA',\n",
       "  'SR',\n",
       "  'ZC',\n",
       "  'CY',\n",
       "  'RM',\n",
       "  'WT',\n",
       "  'PM',\n",
       "  'WH',\n",
       "  'RI',\n",
       "  'OI',\n",
       "  'JR',\n",
       "  'UR',\n",
       "  'LR',\n",
       "  'WS',\n",
       "  'SA',\n",
       "  'AP',\n",
       "  'RS',\n",
       "  'PF',\n",
       "  'ME',\n",
       "  'RO',\n",
       "  'CJ',\n",
       "  'TC',\n",
       "  'ER',\n",
       "  'PK',\n",
       "  'SH',\n",
       "  'PX'],\n",
       " 'CFFEX': ['IF', 'IC', 'IH', 'TF', 'T', 'TS', 'IM', 'TL'],\n",
       " 'INE': ['SC', 'NR', 'SCTAS', 'LU', 'BC', 'EC'],\n",
       " 'GFEX': ['SI', 'LC']}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exchange_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "b9d5ef17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20240229</td>\n",
       "      <td>3774.0</td>\n",
       "      <td>3781.0</td>\n",
       "      <td>3769.0</td>\n",
       "      <td>3774.0</td>\n",
       "      <td>3738.0</td>\n",
       "      <td>3755.0</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>-15.0</td>\n",
       "      <td>10171.0</td>\n",
       "      <td>38309.79</td>\n",
       "      <td>18278.0</td>\n",
       "      <td>-7855.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20240228</td>\n",
       "      <td>3795.0</td>\n",
       "      <td>3755.0</td>\n",
       "      <td>3786.0</td>\n",
       "      <td>3795.0</td>\n",
       "      <td>3769.0</td>\n",
       "      <td>3774.0</td>\n",
       "      <td>3781.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1501.0</td>\n",
       "      <td>5675.29</td>\n",
       "      <td>26133.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20240227</td>\n",
       "      <td>3718.0</td>\n",
       "      <td>3738.0</td>\n",
       "      <td>3720.0</td>\n",
       "      <td>3799.0</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>3795.0</td>\n",
       "      <td>3755.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>6234.78</td>\n",
       "      <td>26088.0</td>\n",
       "      <td>-192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20240226</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>3773.0</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>3771.0</td>\n",
       "      <td>3711.0</td>\n",
       "      <td>3718.0</td>\n",
       "      <td>3738.0</td>\n",
       "      <td>-55.0</td>\n",
       "      <td>-35.0</td>\n",
       "      <td>3213.0</td>\n",
       "      <td>12011.66</td>\n",
       "      <td>26280.0</td>\n",
       "      <td>-365.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20240223</td>\n",
       "      <td>3776.0</td>\n",
       "      <td>3771.0</td>\n",
       "      <td>3776.0</td>\n",
       "      <td>3788.0</td>\n",
       "      <td>3757.0</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>3773.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2361.0</td>\n",
       "      <td>8909.86</td>\n",
       "      <td>26645.0</td>\n",
       "      <td>-665.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20230424</td>\n",
       "      <td>3718.0</td>\n",
       "      <td>3752.0</td>\n",
       "      <td>3724.0</td>\n",
       "      <td>3724.0</td>\n",
       "      <td>3611.0</td>\n",
       "      <td>3633.0</td>\n",
       "      <td>3659.0</td>\n",
       "      <td>-119.0</td>\n",
       "      <td>-93.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>537.90</td>\n",
       "      <td>195.0</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20230421</td>\n",
       "      <td>3810.0</td>\n",
       "      <td>3796.0</td>\n",
       "      <td>3784.0</td>\n",
       "      <td>3787.0</td>\n",
       "      <td>3718.0</td>\n",
       "      <td>3718.0</td>\n",
       "      <td>3752.0</td>\n",
       "      <td>-78.0</td>\n",
       "      <td>-44.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>296.47</td>\n",
       "      <td>85.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20230420</td>\n",
       "      <td>3802.0</td>\n",
       "      <td>3834.0</td>\n",
       "      <td>3801.0</td>\n",
       "      <td>3810.0</td>\n",
       "      <td>3773.0</td>\n",
       "      <td>3810.0</td>\n",
       "      <td>3796.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>-38.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>98.70</td>\n",
       "      <td>23.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20230419</td>\n",
       "      <td>3833.0</td>\n",
       "      <td>3843.0</td>\n",
       "      <td>3848.0</td>\n",
       "      <td>3852.0</td>\n",
       "      <td>3802.0</td>\n",
       "      <td>3802.0</td>\n",
       "      <td>3834.0</td>\n",
       "      <td>-41.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>30.67</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>RB2404.SHF</td>\n",
       "      <td>20230418</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3797.0</td>\n",
       "      <td>3857.0</td>\n",
       "      <td>3866.0</td>\n",
       "      <td>3830.0</td>\n",
       "      <td>3833.0</td>\n",
       "      <td>3843.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>34.59</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ts_code trade_date  pre_close  pre_settle    open    high     low  \\\n",
       "0    RB2404.SHF   20240229     3774.0      3781.0  3769.0  3774.0  3738.0   \n",
       "1    RB2404.SHF   20240228     3795.0      3755.0  3786.0  3795.0  3769.0   \n",
       "2    RB2404.SHF   20240227     3718.0      3738.0  3720.0  3799.0  3715.0   \n",
       "3    RB2404.SHF   20240226     3766.0      3773.0  3766.0  3771.0  3711.0   \n",
       "4    RB2404.SHF   20240223     3776.0      3771.0  3776.0  3788.0  3757.0   \n",
       "..          ...        ...        ...         ...     ...     ...     ...   \n",
       "205  RB2404.SHF   20230424     3718.0      3752.0  3724.0  3724.0  3611.0   \n",
       "206  RB2404.SHF   20230421     3810.0      3796.0  3784.0  3787.0  3718.0   \n",
       "207  RB2404.SHF   20230420     3802.0      3834.0  3801.0  3810.0  3773.0   \n",
       "208  RB2404.SHF   20230419     3833.0      3843.0  3848.0  3852.0  3802.0   \n",
       "209  RB2404.SHF   20230418        NaN      3797.0  3857.0  3866.0  3830.0   \n",
       "\n",
       "      close  settle  change1  change2      vol    amount       oi  oi_chg  \n",
       "0    3755.0  3766.0    -26.0    -15.0  10171.0  38309.79  18278.0 -7855.0  \n",
       "1    3774.0  3781.0     19.0     26.0   1501.0   5675.29  26133.0    45.0  \n",
       "2    3795.0  3755.0     57.0     17.0   1660.0   6234.78  26088.0  -192.0  \n",
       "3    3718.0  3738.0    -55.0    -35.0   3213.0  12011.66  26280.0  -365.0  \n",
       "4    3766.0  3773.0     -5.0      2.0   2361.0   8909.86  26645.0  -665.0  \n",
       "..      ...     ...      ...      ...      ...       ...      ...     ...  \n",
       "205  3633.0  3659.0   -119.0    -93.0    147.0    537.90    195.0   110.0  \n",
       "206  3718.0  3752.0    -78.0    -44.0     79.0    296.47     85.0    62.0  \n",
       "207  3810.0  3796.0    -24.0    -38.0     26.0     98.70     23.0    10.0  \n",
       "208  3802.0  3834.0    -41.0     -9.0      8.0     30.67     13.0     7.0  \n",
       "209  3833.0  3843.0     36.0     46.0      9.0     34.59      6.0     NaN  \n",
       "\n",
       "[210 rows x 15 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd = pro.fut_daily(ts_code='RB2404.SHF')\n",
    "dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6e92eac3",
   "metadata": {},
   "outputs": [],
   "source": [
    "上次更新时间 = '2024-01-01'\n",
    "\n",
    "需要更新增量数据的合约 = df_所有合约[df_所有合约['delist_date'] >= 上次更新时间]['ts_code'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9de3d6be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['A2401.DCE',\n",
       " 'A2403.DCE',\n",
       " 'A2405.DCE',\n",
       " 'A2407.DCE',\n",
       " 'A2409.DCE',\n",
       " 'A2411.DCE',\n",
       " 'A2501.DCE',\n",
       " 'AG2401.SHF',\n",
       " 'AG2402.SHF',\n",
       " 'AG2403.SHF',\n",
       " 'AG2404.SHF',\n",
       " 'AG2405.SHF',\n",
       " 'AG2406.SHF',\n",
       " 'AG2407.SHF',\n",
       " 'AG2408.SHF',\n",
       " 'AG2409.SHF',\n",
       " 'AG2410.SHF',\n",
       " 'AG2411.SHF',\n",
       " 'AG2412.SHF',\n",
       " 'AG2501.SHF',\n",
       " 'AG2502.SHF',\n",
       " 'AL2401.SHF',\n",
       " 'AL2402.SHF',\n",
       " 'AL2403.SHF',\n",
       " 'AL2404.SHF',\n",
       " 'AL2405.SHF',\n",
       " 'AL2406.SHF',\n",
       " 'AL2407.SHF',\n",
       " 'AL2408.SHF',\n",
       " 'AL2409.SHF',\n",
       " 'AL2410.SHF',\n",
       " 'AL2411.SHF',\n",
       " 'AL2412.SHF',\n",
       " 'AL2501.SHF',\n",
       " 'AL2502.SHF',\n",
       " 'AO2401.SHF',\n",
       " 'AO2402.SHF',\n",
       " 'AO2403.SHF',\n",
       " 'AO2404.SHF',\n",
       " 'AO2405.SHF',\n",
       " 'AO2406.SHF',\n",
       " 'AO2407.SHF',\n",
       " 'AO2408.SHF',\n",
       " 'AO2409.SHF',\n",
       " 'AO2410.SHF',\n",
       " 'AO2411.SHF',\n",
       " 'AO2412.SHF',\n",
       " 'AO2501.SHF',\n",
       " 'AO2502.SHF',\n",
       " 'AP2401.ZCE',\n",
       " 'AP2403.ZCE',\n",
       " 'AP2404.ZCE',\n",
       " 'AP2405.ZCE',\n",
       " 'AP2410.ZCE',\n",
       " 'AP2411.ZCE',\n",
       " 'AP2412.ZCE',\n",
       " 'AP2501.ZCE',\n",
       " 'AU2401.SHF',\n",
       " 'AU2402.SHF',\n",
       " 'AU2403.SHF',\n",
       " 'AU2404.SHF',\n",
       " 'AU2405.SHF',\n",
       " 'AU2406.SHF',\n",
       " 'AU2408.SHF',\n",
       " 'AU2410.SHF',\n",
       " 'AU2412.SHF',\n",
       " 'AU2502.SHF',\n",
       " 'B2401.DCE',\n",
       " 'B2402.DCE',\n",
       " 'B2403.DCE',\n",
       " 'B2404.DCE',\n",
       " 'B2405.DCE',\n",
       " 'B2406.DCE',\n",
       " 'B2407.DCE',\n",
       " 'B2408.DCE',\n",
       " 'B2409.DCE',\n",
       " 'B2410.DCE',\n",
       " 'B2411.DCE',\n",
       " 'B2412.DCE',\n",
       " 'B2501.DCE',\n",
       " 'B2502.DCE',\n",
       " 'BB2401.DCE',\n",
       " 'BB2402.DCE',\n",
       " 'BB2403.DCE',\n",
       " 'BB2404.DCE',\n",
       " 'BB2405.DCE',\n",
       " 'BB2406.DCE',\n",
       " 'BB2407.DCE',\n",
       " 'BB2408.DCE',\n",
       " 'BB2409.DCE',\n",
       " 'BB2410.DCE',\n",
       " 'BB2411.DCE',\n",
       " 'BB2412.DCE',\n",
       " 'BB2501.DCE',\n",
       " 'BB2502.DCE',\n",
       " 'BC2401.INE',\n",
       " 'BC2402.INE',\n",
       " 'BC2403.INE',\n",
       " 'BC2404.INE',\n",
       " 'BC2405.INE',\n",
       " 'BC2406.INE',\n",
       " 'BC2407.INE',\n",
       " 'BC2408.INE',\n",
       " 'BC2409.INE',\n",
       " 'BC2410.INE',\n",
       " 'BC2411.INE',\n",
       " 'BC2412.INE',\n",
       " 'BC2501.INE',\n",
       " 'BC2502.INE',\n",
       " 'BR2401.SHF',\n",
       " 'BR2402.SHF',\n",
       " 'BR2403.SHF',\n",
       " 'BR2404.SHF',\n",
       " 'BR2405.SHF',\n",
       " 'BR2406.SHF',\n",
       " 'BR2407.SHF',\n",
       " 'BR2408.SHF',\n",
       " 'BR2409.SHF',\n",
       " 'BR2410.SHF',\n",
       " 'BR2411.SHF',\n",
       " 'BR2412.SHF',\n",
       " 'BR2501.SHF',\n",
       " 'BR2502.SHF',\n",
       " 'BU2401.SHF',\n",
       " 'BU2402.SHF',\n",
       " 'BU2403.SHF',\n",
       " 'BU2404.SHF',\n",
       " 'BU2405.SHF',\n",
       " 'BU2406.SHF',\n",
       " 'BU2407.SHF',\n",
       " 'BU2408.SHF',\n",
       " 'BU2409.SHF',\n",
       " 'BU2410.SHF',\n",
       " 'BU2411.SHF',\n",
       " 'BU2412.SHF',\n",
       " 'BU2501.SHF',\n",
       " 'BU2502.SHF',\n",
       " 'BU2503.SHF',\n",
       " 'BU2506.SHF',\n",
       " 'BU2509.SHF',\n",
       " 'BU2512.SHF',\n",
       " 'C2401.DCE',\n",
       " 'C2403.DCE',\n",
       " 'C2405.DCE',\n",
       " 'C2407.DCE',\n",
       " 'C2409.DCE',\n",
       " 'C2411.DCE',\n",
       " 'C2501.DCE',\n",
       " 'CF2401.ZCE',\n",
       " 'CF2403.ZCE',\n",
       " 'CF2405.ZCE',\n",
       " 'CF2407.ZCE',\n",
       " 'CF2409.ZCE',\n",
       " 'CF2411.ZCE',\n",
       " 'CF2501.ZCE',\n",
       " 'CJ2401.ZCE',\n",
       " 'CJ2403.ZCE',\n",
       " 'CJ2405.ZCE',\n",
       " 'CJ2407.ZCE',\n",
       " 'CJ2409.ZCE',\n",
       " 'CJ2412.ZCE',\n",
       " 'CJ2501.ZCE',\n",
       " 'CS2401.DCE',\n",
       " 'CS2403.DCE',\n",
       " 'CS2405.DCE',\n",
       " 'CS2407.DCE',\n",
       " 'CS2409.DCE',\n",
       " 'CS2411.DCE',\n",
       " 'CS2501.DCE',\n",
       " 'CU2401.SHF',\n",
       " 'CU2402.SHF',\n",
       " 'CU2403.SHF',\n",
       " 'CU2404.SHF',\n",
       " 'CU2405.SHF',\n",
       " 'CU2406.SHF',\n",
       " 'CU2407.SHF',\n",
       " 'CU2408.SHF',\n",
       " 'CU2409.SHF',\n",
       " 'CU2410.SHF',\n",
       " 'CU2411.SHF',\n",
       " 'CU2412.SHF',\n",
       " 'CU2501.SHF',\n",
       " 'CU2502.SHF',\n",
       " 'CY2401.ZCE',\n",
       " 'CY2402.ZCE',\n",
       " 'CY2403.ZCE',\n",
       " 'CY2404.ZCE',\n",
       " 'CY2405.ZCE',\n",
       " 'CY2406.ZCE',\n",
       " 'CY2407.ZCE',\n",
       " 'CY2408.ZCE',\n",
       " 'CY2409.ZCE',\n",
       " 'CY2410.ZCE',\n",
       " 'CY2411.ZCE',\n",
       " 'CY2412.ZCE',\n",
       " 'CY2501.ZCE',\n",
       " 'CY2502.ZCE',\n",
       " 'EB2401.DCE',\n",
       " 'EB2402.DCE',\n",
       " 'EB2403.DCE',\n",
       " 'EB2404.DCE',\n",
       " 'EB2405.DCE',\n",
       " 'EB2406.DCE',\n",
       " 'EB2407.DCE',\n",
       " 'EB2408.DCE',\n",
       " 'EB2409.DCE',\n",
       " 'EB2410.DCE',\n",
       " 'EB2411.DCE',\n",
       " 'EB2412.DCE',\n",
       " 'EB2501.DCE',\n",
       " 'EB2502.DCE',\n",
       " 'EC2404.INE',\n",
       " 'EC2406.INE',\n",
       " 'EC2408.INE',\n",
       " 'EC2410.INE',\n",
       " 'EC2412.INE',\n",
       " 'EC2502.INE',\n",
       " 'EG2401.DCE',\n",
       " 'EG2402.DCE',\n",
       " 'EG2403.DCE',\n",
       " 'EG2404.DCE',\n",
       " 'EG2405.DCE',\n",
       " 'EG2406.DCE',\n",
       " 'EG2407.DCE',\n",
       " 'EG2408.DCE',\n",
       " 'EG2409.DCE',\n",
       " 'EG2410.DCE',\n",
       " 'EG2411.DCE',\n",
       " 'EG2412.DCE',\n",
       " 'EG2501.DCE',\n",
       " 'EG2502.DCE',\n",
       " 'FB2401.DCE',\n",
       " 'FB2402.DCE',\n",
       " 'FB2403.DCE',\n",
       " 'FB2404.DCE',\n",
       " 'FB2405.DCE',\n",
       " 'FB2406.DCE',\n",
       " 'FB2407.DCE',\n",
       " 'FB2408.DCE',\n",
       " 'FB2409.DCE',\n",
       " 'FB2410.DCE',\n",
       " 'FB2411.DCE',\n",
       " 'FB2412.DCE',\n",
       " 'FB2501.DCE',\n",
       " 'FB2502.DCE',\n",
       " 'FG2401.ZCE',\n",
       " 'FG2402.ZCE',\n",
       " 'FG2403.ZCE',\n",
       " 'FG2404.ZCE',\n",
       " 'FG2405.ZCE',\n",
       " 'FG2406.ZCE',\n",
       " 'FG2407.ZCE',\n",
       " 'FG2408.ZCE',\n",
       " 'FG2409.ZCE',\n",
       " 'FG2410.ZCE',\n",
       " 'FG2411.ZCE',\n",
       " 'FG2412.ZCE',\n",
       " 'FG2501.ZCE',\n",
       " 'FG2502.ZCE',\n",
       " 'FU2402.SHF',\n",
       " 'FU2403.SHF',\n",
       " 'FU2404.SHF',\n",
       " 'FU2405.SHF',\n",
       " 'FU2406.SHF',\n",
       " 'FU2407.SHF',\n",
       " 'FU2408.SHF',\n",
       " 'FU2409.SHF',\n",
       " 'FU2410.SHF',\n",
       " 'FU2411.SHF',\n",
       " 'FU2412.SHF',\n",
       " 'FU2501.SHF',\n",
       " 'FU2502.SHF',\n",
       " 'HC2401.SHF',\n",
       " 'HC2402.SHF',\n",
       " 'HC2403.SHF',\n",
       " 'HC2404.SHF',\n",
       " 'HC2405.SHF',\n",
       " 'HC2406.SHF',\n",
       " 'HC2407.SHF',\n",
       " 'HC2408.SHF',\n",
       " 'HC2409.SHF',\n",
       " 'HC2410.SHF',\n",
       " 'HC2411.SHF',\n",
       " 'HC2412.SHF',\n",
       " 'HC2501.SHF',\n",
       " 'HC2502.SHF',\n",
       " 'I2401.DCE',\n",
       " 'I2402.DCE',\n",
       " 'I2403.DCE',\n",
       " 'I2404.DCE',\n",
       " 'I2405.DCE',\n",
       " 'I2406.DCE',\n",
       " 'I2407.DCE',\n",
       " 'I2408.DCE',\n",
       " 'I2409.DCE',\n",
       " 'I2410.DCE',\n",
       " 'I2411.DCE',\n",
       " 'I2412.DCE',\n",
       " 'I2501.DCE',\n",
       " 'I2502.DCE',\n",
       " 'IC2401.CFX',\n",
       " 'IC2402.CFX',\n",
       " 'IC2403.CFX',\n",
       " 'IC2404.CFX',\n",
       " 'IC2406.CFX',\n",
       " 'IC2409.CFX',\n",
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       " 'IF2403.CFX',\n",
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       " 'IF2406.CFX',\n",
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       " 'IH2401.CFX',\n",
       " 'IH2402.CFX',\n",
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       " 'IH2404.CFX',\n",
       " 'IH2406.CFX',\n",
       " 'IH2409.CFX',\n",
       " 'IM2401.CFX',\n",
       " 'IM2402.CFX',\n",
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       " 'IM2404.CFX',\n",
       " 'IM2406.CFX',\n",
       " 'IM2409.CFX',\n",
       " 'J2401.DCE',\n",
       " 'J2402.DCE',\n",
       " 'J2403.DCE',\n",
       " 'J2404.DCE',\n",
       " 'J2405.DCE',\n",
       " 'J2406.DCE',\n",
       " 'J2407.DCE',\n",
       " 'J2408.DCE',\n",
       " 'J2409.DCE',\n",
       " 'J2410.DCE',\n",
       " 'J2411.DCE',\n",
       " 'J2412.DCE',\n",
       " 'J2501.DCE',\n",
       " 'J2502.DCE',\n",
       " 'JD2401.DCE',\n",
       " 'JD2402.DCE',\n",
       " 'JD2403.DCE',\n",
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       " 'JD2409.DCE',\n",
       " 'JD2410.DCE',\n",
       " 'JD2411.DCE',\n",
       " 'JD2412.DCE',\n",
       " 'JD2501.DCE',\n",
       " 'JD2502.DCE',\n",
       " 'JM2401.DCE',\n",
       " 'JM2402.DCE',\n",
       " 'JM2403.DCE',\n",
       " 'JM2404.DCE',\n",
       " 'JM2405.DCE',\n",
       " 'JM2406.DCE',\n",
       " 'JM2407.DCE',\n",
       " 'JM2408.DCE',\n",
       " 'JM2409.DCE',\n",
       " 'JM2410.DCE',\n",
       " 'JM2411.DCE',\n",
       " 'JM2412.DCE',\n",
       " 'JM2501.DCE',\n",
       " 'JM2502.DCE',\n",
       " 'JR2401.ZCE',\n",
       " 'JR2403.ZCE',\n",
       " 'JR2405.ZCE',\n",
       " 'JR2407.ZCE',\n",
       " 'JR2409.ZCE',\n",
       " 'JR2411.ZCE',\n",
       " 'JR2501.ZCE',\n",
       " 'L2401.DCE',\n",
       " 'L2402.DCE',\n",
       " 'L2403.DCE',\n",
       " 'L2404.DCE',\n",
       " 'L2405.DCE',\n",
       " 'L2406.DCE',\n",
       " 'L2407.DCE',\n",
       " 'L2408.DCE',\n",
       " 'L2409.DCE',\n",
       " 'L2410.DCE',\n",
       " 'L2411.DCE',\n",
       " 'L2412.DCE',\n",
       " 'L2501.DCE',\n",
       " 'L2502.DCE',\n",
       " 'LC2401.GFE',\n",
       " 'LC2402.GFE',\n",
       " 'LC2403.GFE',\n",
       " 'LC2404.GFE',\n",
       " 'LC2405.GFE',\n",
       " 'LC2406.GFE',\n",
       " 'LC2407.GFE',\n",
       " 'LC2408.GFE',\n",
       " 'LC2409.GFE',\n",
       " 'LC2410.GFE',\n",
       " 'LC2411.GFE',\n",
       " 'LC2412.GFE',\n",
       " 'LC2501.GFE',\n",
       " 'LC2502.GFE',\n",
       " 'LH2401.DCE',\n",
       " 'LH2403.DCE',\n",
       " 'LH2405.DCE',\n",
       " 'LH2407.DCE',\n",
       " 'LH2409.DCE',\n",
       " 'LH2411.DCE',\n",
       " 'LH2501.DCE',\n",
       " 'LR2401.ZCE',\n",
       " 'LR2403.ZCE',\n",
       " 'LR2405.ZCE',\n",
       " 'LR2407.ZCE',\n",
       " 'LR2409.ZCE',\n",
       " 'LR2411.ZCE',\n",
       " 'LR2501.ZCE',\n",
       " 'LU2402.INE',\n",
       " 'LU2403.INE',\n",
       " 'LU2404.INE',\n",
       " 'LU2405.INE',\n",
       " 'LU2406.INE',\n",
       " 'LU2407.INE',\n",
       " 'LU2408.INE',\n",
       " 'LU2409.INE',\n",
       " 'LU2410.INE',\n",
       " 'LU2411.INE',\n",
       " 'LU2412.INE',\n",
       " 'LU2501.INE',\n",
       " 'LU2502.INE',\n",
       " 'M2401.DCE',\n",
       " 'M2403.DCE',\n",
       " 'M2405.DCE',\n",
       " 'M2407.DCE',\n",
       " 'M2408.DCE',\n",
       " 'M2409.DCE',\n",
       " 'M2411.DCE',\n",
       " 'M2412.DCE',\n",
       " 'M2501.DCE',\n",
       " 'MA2401.ZCE',\n",
       " 'MA2402.ZCE',\n",
       " 'MA2403.ZCE',\n",
       " 'MA2404.ZCE',\n",
       " 'MA2405.ZCE',\n",
       " 'MA2406.ZCE',\n",
       " 'MA2407.ZCE',\n",
       " 'MA2408.ZCE',\n",
       " 'MA2409.ZCE',\n",
       " 'MA2410.ZCE',\n",
       " 'MA2411.ZCE',\n",
       " 'MA2412.ZCE',\n",
       " 'MA2501.ZCE',\n",
       " 'MA2502.ZCE',\n",
       " 'NI2401.SHF',\n",
       " 'NI2402.SHF',\n",
       " 'NI2403.SHF',\n",
       " 'NI2404.SHF',\n",
       " 'NI2405.SHF',\n",
       " 'NI2406.SHF',\n",
       " 'NI2407.SHF',\n",
       " 'NI2408.SHF',\n",
       " 'NI2409.SHF',\n",
       " 'NI2410.SHF',\n",
       " 'NI2411.SHF',\n",
       " 'NI2412.SHF',\n",
       " 'NI2501.SHF',\n",
       " 'NI2502.SHF',\n",
       " 'NR2401.INE',\n",
       " 'NR2402.INE',\n",
       " 'NR2403.INE',\n",
       " 'NR2404.INE',\n",
       " 'NR2405.INE',\n",
       " 'NR2406.INE',\n",
       " 'NR2407.INE',\n",
       " 'NR2408.INE',\n",
       " 'NR2409.INE',\n",
       " 'NR2410.INE',\n",
       " 'NR2411.INE',\n",
       " 'NR2412.INE',\n",
       " 'NR2501.INE',\n",
       " 'NR2502.INE',\n",
       " 'OI2401.ZCE',\n",
       " 'OI2403.ZCE',\n",
       " 'OI2405.ZCE',\n",
       " 'OI2407.ZCE',\n",
       " 'OI2409.ZCE',\n",
       " 'OI2411.ZCE',\n",
       " 'OI2501.ZCE',\n",
       " 'P2401.DCE',\n",
       " 'P2402.DCE',\n",
       " 'P2403.DCE',\n",
       " 'P2404.DCE',\n",
       " 'P2405.DCE',\n",
       " 'P2406.DCE',\n",
       " 'P2407.DCE',\n",
       " 'P2408.DCE',\n",
       " 'P2409.DCE',\n",
       " 'P2410.DCE',\n",
       " 'P2411.DCE',\n",
       " 'P2412.DCE',\n",
       " 'P2501.DCE',\n",
       " 'P2502.DCE',\n",
       " 'PB2401.SHF',\n",
       " 'PB2402.SHF',\n",
       " 'PB2403.SHF',\n",
       " 'PB2404.SHF',\n",
       " 'PB2405.SHF',\n",
       " 'PB2406.SHF',\n",
       " 'PB2407.SHF',\n",
       " 'PB2408.SHF',\n",
       " 'PB2409.SHF',\n",
       " 'PB2410.SHF',\n",
       " 'PB2411.SHF',\n",
       " 'PB2412.SHF',\n",
       " 'PB2501.SHF',\n",
       " 'PB2502.SHF',\n",
       " 'PF2401.ZCE',\n",
       " 'PF2402.ZCE',\n",
       " 'PF2403.ZCE',\n",
       " 'PF2404.ZCE',\n",
       " 'PF2405.ZCE',\n",
       " 'PF2406.ZCE',\n",
       " 'PF2407.ZCE',\n",
       " 'PF2408.ZCE',\n",
       " 'PF2409.ZCE',\n",
       " 'PF2410.ZCE',\n",
       " 'PF2411.ZCE',\n",
       " 'PF2412.ZCE',\n",
       " 'PF2501.ZCE',\n",
       " 'PF2502.ZCE',\n",
       " 'PG2401.DCE',\n",
       " 'PG2402.DCE',\n",
       " 'PG2403.DCE',\n",
       " 'PG2404.DCE',\n",
       " 'PG2405.DCE',\n",
       " 'PG2406.DCE',\n",
       " 'PG2407.DCE',\n",
       " 'PG2408.DCE',\n",
       " 'PG2409.DCE',\n",
       " 'PG2410.DCE',\n",
       " 'PG2411.DCE',\n",
       " 'PG2412.DCE',\n",
       " 'PG2501.DCE',\n",
       " 'PG2502.DCE',\n",
       " 'PK2401.ZCE',\n",
       " 'PK2403.ZCE',\n",
       " 'PK2404.ZCE',\n",
       " 'PK2410.ZCE',\n",
       " 'PK2411.ZCE',\n",
       " 'PK2412.ZCE',\n",
       " 'PK2501.ZCE',\n",
       " 'PM2401.ZCE',\n",
       " 'PM2403.ZCE',\n",
       " 'PM2405.ZCE',\n",
       " 'PM2407.ZCE',\n",
       " 'PM2409.ZCE',\n",
       " 'PM2411.ZCE',\n",
       " 'PM2501.ZCE',\n",
       " 'PP2401.DCE',\n",
       " 'PP2402.DCE',\n",
       " 'PP2403.DCE',\n",
       " 'PP2404.DCE',\n",
       " 'PP2405.DCE',\n",
       " 'PP2406.DCE',\n",
       " 'PP2407.DCE',\n",
       " 'PP2408.DCE',\n",
       " 'PP2409.DCE',\n",
       " 'PP2410.DCE',\n",
       " 'PP2411.DCE',\n",
       " 'PP2412.DCE',\n",
       " 'PP2501.DCE',\n",
       " 'PP2502.DCE',\n",
       " 'PX2405.ZCE',\n",
       " 'PX2406.ZCE',\n",
       " 'PX2407.ZCE',\n",
       " 'PX2408.ZCE',\n",
       " 'PX2409.ZCE',\n",
       " 'PX2410.ZCE',\n",
       " 'PX2411.ZCE',\n",
       " 'PX2412.ZCE',\n",
       " 'PX2501.ZCE',\n",
       " 'PX2502.ZCE',\n",
       " 'RB2401.SHF',\n",
       " 'RB2402.SHF',\n",
       " 'RB2403.SHF',\n",
       " 'RB2404.SHF',\n",
       " 'RB2405.SHF',\n",
       " 'RB2406.SHF',\n",
       " 'RB2407.SHF',\n",
       " 'RB2408.SHF',\n",
       " 'RB2409.SHF',\n",
       " 'RB2410.SHF',\n",
       " 'RB2411.SHF',\n",
       " 'RB2412.SHF',\n",
       " 'RB2501.SHF',\n",
       " 'RB2502.SHF',\n",
       " 'RI2401.ZCE',\n",
       " 'RI2403.ZCE',\n",
       " 'RI2405.ZCE',\n",
       " 'RI2407.ZCE',\n",
       " 'RI2409.ZCE',\n",
       " 'RI2411.ZCE',\n",
       " 'RI2501.ZCE',\n",
       " 'RM2401.ZCE',\n",
       " 'RM2403.ZCE',\n",
       " 'RM2405.ZCE',\n",
       " 'RM2407.ZCE',\n",
       " 'RM2408.ZCE',\n",
       " 'RM2409.ZCE',\n",
       " 'RM2411.ZCE',\n",
       " 'RM2501.ZCE',\n",
       " 'RR2401.DCE',\n",
       " 'RR2402.DCE',\n",
       " 'RR2403.DCE',\n",
       " 'RR2404.DCE',\n",
       " 'RR2405.DCE',\n",
       " 'RR2406.DCE',\n",
       " 'RR2407.DCE',\n",
       " 'RR2408.DCE',\n",
       " 'RR2409.DCE',\n",
       " 'RR2410.DCE',\n",
       " 'RR2411.DCE',\n",
       " 'RR2412.DCE',\n",
       " 'RR2501.DCE',\n",
       " 'RR2502.DCE',\n",
       " 'RS2407.ZCE',\n",
       " 'RS2408.ZCE',\n",
       " 'RS2409.ZCE',\n",
       " 'RS2411.ZCE',\n",
       " 'RU2401.SHF',\n",
       " 'RU2403.SHF',\n",
       " 'RU2404.SHF',\n",
       " 'RU2405.SHF',\n",
       " 'RU2406.SHF',\n",
       " 'RU2407.SHF',\n",
       " 'RU2408.SHF',\n",
       " 'RU2409.SHF',\n",
       " 'RU2410.SHF',\n",
       " 'RU2411.SHF',\n",
       " 'RU2501.SHF',\n",
       " 'SA2401.ZCE',\n",
       " 'SA2402.ZCE',\n",
       " 'SA2403.ZCE',\n",
       " 'SA2404.ZCE',\n",
       " 'SA2405.ZCE',\n",
       " 'SA2406.ZCE',\n",
       " 'SA2407.ZCE',\n",
       " 'SA2408.ZCE',\n",
       " 'SA2409.ZCE',\n",
       " 'SA2410.ZCE',\n",
       " 'SA2411.ZCE',\n",
       " 'SA2412.ZCE',\n",
       " 'SA2501.ZCE',\n",
       " 'SA2502.ZCE',\n",
       " 'SC2402.INE',\n",
       " 'SC2403.INE',\n",
       " 'SC2404.INE',\n",
       " 'SC2405.INE',\n",
       " 'SC2406.INE',\n",
       " 'SC2407.INE',\n",
       " 'SC2408.INE',\n",
       " 'SC2409.INE',\n",
       " 'SC2410.INE',\n",
       " 'SC2411.INE',\n",
       " 'SC2412.INE',\n",
       " 'SC2501.INE',\n",
       " 'SC2502.INE',\n",
       " 'SC2503.INE',\n",
       " 'SC2506.INE',\n",
       " 'SC2509.INE',\n",
       " 'SC2512.INE',\n",
       " 'SC2603.INE',\n",
       " 'SC2606.INE',\n",
       " 'SC2609.INE',\n",
       " 'SC2612.INE',\n",
       " 'SCTAS2402.INE',\n",
       " 'SCTAS2403.INE',\n",
       " 'SCTAS2404.INE',\n",
       " 'SCTAS2405.INE',\n",
       " 'SCTAS2406.INE',\n",
       " 'SF2401.ZCE',\n",
       " 'SF2402.ZCE',\n",
       " 'SF2403.ZCE',\n",
       " 'SF2404.ZCE',\n",
       " 'SF2405.ZCE',\n",
       " 'SF2406.ZCE',\n",
       " 'SF2407.ZCE',\n",
       " 'SF2408.ZCE',\n",
       " 'SF2409.ZCE',\n",
       " 'SF2410.ZCE',\n",
       " 'SF2411.ZCE',\n",
       " 'SF2412.ZCE',\n",
       " 'SF2501.ZCE',\n",
       " 'SF2502.ZCE',\n",
       " 'SH2405.ZCE',\n",
       " 'SH2406.ZCE',\n",
       " 'SH2407.ZCE',\n",
       " 'SH2408.ZCE',\n",
       " 'SH2409.ZCE',\n",
       " 'SH2410.ZCE',\n",
       " 'SH2411.ZCE',\n",
       " 'SH2412.ZCE',\n",
       " 'SH2501.ZCE',\n",
       " 'SH2502.ZCE',\n",
       " 'SI2401.GFE',\n",
       " 'SI2402.GFE',\n",
       " 'SI2403.GFE',\n",
       " 'SI2404.GFE',\n",
       " 'SI2405.GFE',\n",
       " 'SI2406.GFE',\n",
       " 'SI2407.GFE',\n",
       " 'SI2408.GFE',\n",
       " 'SI2409.GFE',\n",
       " 'SI2410.GFE',\n",
       " 'SM2401.ZCE',\n",
       " 'SM2402.ZCE',\n",
       " 'SM2403.ZCE',\n",
       " 'SM2404.ZCE',\n",
       " 'SM2405.ZCE',\n",
       " 'SM2406.ZCE',\n",
       " 'SM2407.ZCE',\n",
       " 'SM2408.ZCE',\n",
       " 'SM2409.ZCE',\n",
       " 'SM2410.ZCE',\n",
       " 'SM2411.ZCE',\n",
       " 'SM2412.ZCE',\n",
       " 'SM2501.ZCE',\n",
       " 'SM2502.ZCE',\n",
       " 'SN2401.SHF',\n",
       " 'SN2402.SHF',\n",
       " 'SN2403.SHF',\n",
       " 'SN2404.SHF',\n",
       " 'SN2405.SHF',\n",
       " 'SN2406.SHF',\n",
       " 'SN2407.SHF',\n",
       " 'SN2408.SHF',\n",
       " 'SN2409.SHF',\n",
       " 'SN2410.SHF',\n",
       " 'SN2411.SHF',\n",
       " 'SN2412.SHF',\n",
       " 'SN2501.SHF',\n",
       " 'SN2502.SHF',\n",
       " 'SP2401.SHF',\n",
       " 'SP2402.SHF',\n",
       " 'SP2403.SHF',\n",
       " 'SP2404.SHF',\n",
       " 'SP2405.SHF',\n",
       " 'SP2406.SHF',\n",
       " 'SP2407.SHF',\n",
       " 'SP2408.SHF',\n",
       " 'SP2409.SHF',\n",
       " 'SP2410.SHF',\n",
       " 'SP2411.SHF',\n",
       " 'SP2412.SHF',\n",
       " 'SP2501.SHF',\n",
       " 'SP2502.SHF',\n",
       " 'SR2401.ZCE',\n",
       " 'SR2403.ZCE',\n",
       " 'SR2405.ZCE',\n",
       " 'SR2407.ZCE',\n",
       " 'SR2409.ZCE',\n",
       " 'SR2411.ZCE',\n",
       " 'SR2501.ZCE',\n",
       " 'SS2401.SHF',\n",
       " 'SS2402.SHF',\n",
       " 'SS2403.SHF',\n",
       " 'SS2404.SHF',\n",
       " 'SS2405.SHF',\n",
       " 'SS2406.SHF',\n",
       " 'SS2407.SHF',\n",
       " 'SS2408.SHF',\n",
       " 'SS2409.SHF',\n",
       " 'SS2410.SHF',\n",
       " 'SS2411.SHF',\n",
       " 'SS2412.SHF',\n",
       " 'SS2501.SHF',\n",
       " 'SS2502.SHF',\n",
       " 'T2403.CFX',\n",
       " 'T2406.CFX',\n",
       " 'T2409.CFX',\n",
       " 'TA2401.ZCE',\n",
       " 'TA2402.ZCE',\n",
       " 'TA2403.ZCE',\n",
       " 'TA2404.ZCE',\n",
       " 'TA2405.ZCE',\n",
       " 'TA2406.ZCE',\n",
       " 'TA2407.ZCE',\n",
       " 'TA2408.ZCE',\n",
       " 'TA2409.ZCE',\n",
       " 'TA2410.ZCE',\n",
       " 'TA2411.ZCE',\n",
       " 'TA2412.ZCE',\n",
       " 'TA2501.ZCE',\n",
       " 'TA2502.ZCE',\n",
       " 'TF2403.CFX',\n",
       " 'TF2406.CFX',\n",
       " 'TF2409.CFX',\n",
       " 'TL2403.CFX',\n",
       " 'TL2406.CFX',\n",
       " 'TL2409.CFX',\n",
       " 'TS2403.CFX',\n",
       " 'TS2406.CFX',\n",
       " 'TS2409.CFX',\n",
       " 'UR2401.ZCE',\n",
       " 'UR2402.ZCE',\n",
       " 'UR2403.ZCE',\n",
       " 'UR2404.ZCE',\n",
       " 'UR2405.ZCE',\n",
       " 'UR2406.ZCE',\n",
       " 'UR2407.ZCE',\n",
       " 'UR2408.ZCE',\n",
       " 'UR2409.ZCE',\n",
       " 'UR2410.ZCE',\n",
       " 'UR2411.ZCE',\n",
       " 'UR2412.ZCE',\n",
       " 'UR2501.ZCE',\n",
       " 'UR2502.ZCE',\n",
       " 'V2401.DCE',\n",
       " 'V2402.DCE',\n",
       " 'V2403.DCE',\n",
       " 'V2404.DCE',\n",
       " 'V2405.DCE',\n",
       " 'V2406.DCE',\n",
       " 'V2407.DCE',\n",
       " 'V2408.DCE',\n",
       " 'V2409.DCE',\n",
       " 'V2410.DCE',\n",
       " 'V2411.DCE',\n",
       " 'V2412.DCE',\n",
       " 'V2501.DCE',\n",
       " 'V2502.DCE',\n",
       " 'WH2401.ZCE',\n",
       " 'WH2403.ZCE',\n",
       " 'WH2405.ZCE',\n",
       " 'WH2407.ZCE',\n",
       " 'WH2409.ZCE',\n",
       " 'WH2411.ZCE',\n",
       " 'WH2501.ZCE',\n",
       " 'WR2401.SHF',\n",
       " 'WR2402.SHF',\n",
       " 'WR2403.SHF',\n",
       " 'WR2404.SHF',\n",
       " 'WR2405.SHF',\n",
       " 'WR2406.SHF',\n",
       " 'WR2407.SHF',\n",
       " 'WR2408.SHF',\n",
       " 'WR2409.SHF',\n",
       " 'WR2410.SHF',\n",
       " 'WR2411.SHF',\n",
       " 'WR2412.SHF',\n",
       " 'WR2501.SHF',\n",
       " 'WR2502.SHF',\n",
       " 'Y2401.DCE',\n",
       " 'Y2403.DCE',\n",
       " 'Y2405.DCE',\n",
       " 'Y2407.DCE',\n",
       " 'Y2408.DCE',\n",
       " 'Y2409.DCE',\n",
       " 'Y2411.DCE',\n",
       " 'Y2412.DCE',\n",
       " 'Y2501.DCE',\n",
       " 'ZC2401.ZCE',\n",
       " 'ZC2402.ZCE',\n",
       " 'ZC2403.ZCE',\n",
       " 'ZC2404.ZCE',\n",
       " 'ZC2405.ZCE',\n",
       " 'ZC2406.ZCE',\n",
       " 'ZC2407.ZCE',\n",
       " 'ZC2408.ZCE',\n",
       " 'ZC2409.ZCE',\n",
       " 'ZC2410.ZCE',\n",
       " 'ZC2411.ZCE',\n",
       " 'ZC2412.ZCE',\n",
       " 'ZC2501.ZCE',\n",
       " 'ZC2502.ZCE',\n",
       " 'ZN2401.SHF',\n",
       " 'ZN2402.SHF',\n",
       " 'ZN2403.SHF',\n",
       " 'ZN2404.SHF',\n",
       " 'ZN2405.SHF',\n",
       " 'ZN2406.SHF',\n",
       " 'ZN2407.SHF',\n",
       " 'ZN2408.SHF',\n",
       " 'ZN2409.SHF',\n",
       " 'ZN2410.SHF',\n",
       " 'ZN2411.SHF',\n",
       " 'ZN2412.SHF',\n",
       " 'ZN2501.SHF',\n",
       " 'ZN2502.SHF']"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "需要更新增量数据的合约"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3023340e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dd7336fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "07e8b08fecfc46ab94a0b44af11130dd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/887 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "更新数据表(需要更新增量数据的合约)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "383b5683",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb8be983",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a3c5a98",
   "metadata": {},
   "outputs": [],
   "source": [
    "def 更新数据表(需要下载的codes):\n",
    "    未成功下载的codes = []\n",
    "    for code in tqdm(需要下载的codes):\n",
    "        for ss in range(10):\n",
    "            try:\n",
    "                table = re.sub(\"\\D\", \"\", code)\n",
    "                期货前缀 = code.split('.')[0].replace(table,'')\n",
    "                db_name = f'{期货前缀}.db'\n",
    "                engine = create_engine(dailydata_db_path + db_name)\n",
    "                sql = text(f\"DROP TABLE IF EXISTS '{table}'\")\n",
    "                engine.execute(sql)\n",
    "                dd = pro.fut_daily(ts_code=code)\n",
    "                dd.rename(columns={'trade_date':'t'}, inplace=True)\n",
    "                dd['t'] = dd['t'].astype(str)\n",
    "                dd.to_sql(table, engine, index=False, if_exists='append')\n",
    "                time.sleep(0.3)\n",
    "                break\n",
    "            except:\n",
    "                logger.info('下载出错，重试中..')\n",
    "                time.sleep(3)\n",
    "            未成功下载的codes.append(code)\n",
    "    return 未成功下载的codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30f4e15c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe2f9c64",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b5e7f539",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2025520d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24b09c64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3528b21af48541a59f497538d2d32b73",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/880 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dailydata_db_path = f'sqlite:////tushare_database/dailydata/'\n",
    "def 更新数据表(需要下载的codes):\n",
    "    未成功下载的codes = []\n",
    "    for code in tqdm(需要更新增量数据的合约):\n",
    "        for ss in range(10):\n",
    "            try:\n",
    "                table = re.sub(\"\\D\", \"\", code)\n",
    "                期货前缀 = code.split('.')[0].replace(table,'')\n",
    "                db_name = f'{期货前缀}.db'\n",
    "                engine = create_engine(dailydata_db_path + db_name)\n",
    "                sql = text(f\"DROP TABLE IF EXISTS '{table}'\")\n",
    "                engine.execute(sql)\n",
    "                dd = pro.fut_daily(ts_code=code)\n",
    "                dd.to_sql(table, engine, index=False, if_exists='append')\n",
    "                time.sleep(0.3)\n",
    "                break\n",
    "            except:\n",
    "                logger.info('下载出错，重试中..')\n",
    "                time.sleep(3)\n",
    "            未成功下载的codes.append(code)\n",
    "    return 未成功下载的codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7dc5519b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33f648c2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb07b382",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d98fffe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a6d78e99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6d9fad50235348e2a499ba2f29a20386",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/86 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df_cat = get_cat()\n",
    "期货前缀ss = os.listdir('D:/tushare_database/dailydata')\n",
    "期货前缀ss = [x.split('.')[0] for x in 期货前缀ss]\n",
    "# 期货前缀ss = list(set(期货前缀ss) - set(list(df_cat[df_cat['category']=='fin'].index)))\n",
    "\n",
    "期货前缀ss2 = []\n",
    "for 期货前缀 in tqdm(期货前缀ss):\n",
    "    df = get_df(期货前缀)\n",
    "    df_close = df.pivot(index='t', columns='code', values='close')\n",
    "#     if (df_close.notnull().sum(1) != 0).sum() > 250 and df_close.columns[-1] > '2301':\n",
    "    if (df_close.notnull().sum(1) != 0).sum() > 250:\n",
    "        期货前缀ss2.append(期货前缀)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0aae1b70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0285a3d786e445b4831bc1e290def87a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/77 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ddds = []\n",
    "for 期货前缀 in tqdm(期货前缀ss2):\n",
    "    df = get_df(期货前缀)\n",
    "    df_open = df.pivot(index='t', columns='code', values='open')\n",
    "    df_high = df.pivot(index='t', columns='code', values='high')\n",
    "    df_low = df.pivot(index='t', columns='code', values='low')\n",
    "    df_close = df.pivot(index='t', columns='code', values='close')\n",
    "    df_money = df.pivot(index='t', columns='code', values='amount')\n",
    "    df_money_ratio = df_money.div(df_money.sum(1),axis=0)\n",
    "    df_oi = df.pivot(index='t', columns='code', values='oi')\n",
    "    dd_amount = df.pivot(index='t',columns='code',values='amount')\n",
    "    当前主力代码 = pd.Series(dd_amount.columns[np.argsort(-dd_amount.values,axis=1)[:,0]],\n",
    "                       index=dd_amount.index).shift(1)\n",
    "    ddd = pd.concat([\n",
    "        当前主力代码,\n",
    "        df_close.apply(lambda x: x.get(当前主力代码.get(x.name)), axis=1),\n",
    "        df_close.pct_change().apply(lambda x: x.get(当前主力代码.get(x.name)), axis=1),\n",
    "        df_money.apply(lambda x: x.get(当前主力代码.get(x.name)), axis=1),\n",
    "    ],axis=1)\n",
    "    ddd.columns = ['主力代码','主力close','主力代码收益率','主力交易额']\n",
    "    ddds.append(ddd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "39e03dd3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dff = pd.concat([x['主力代码收益率'] for x in ddds],axis=1)\n",
    "dff.columns = 期货前缀ss2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a78d4a83",
   "metadata": {},
   "outputs": [],
   "source": [
    "code = 'USDCNH.FXCM'\n",
    "dd_fx = pro.fx_daily(ts_code=code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8c6e473e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>bid_open</th>\n",
       "      <th>bid_close</th>\n",
       "      <th>bid_high</th>\n",
       "      <th>bid_low</th>\n",
       "      <th>ask_open</th>\n",
       "      <th>ask_close</th>\n",
       "      <th>ask_high</th>\n",
       "      <th>ask_low</th>\n",
       "      <th>tick_qty</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20231204</td>\n",
       "      <td>7.14628</td>\n",
       "      <td>7.15025</td>\n",
       "      <td>7.15353</td>\n",
       "      <td>7.14412</td>\n",
       "      <td>7.15292</td>\n",
       "      <td>7.15097</td>\n",
       "      <td>7.15430</td>\n",
       "      <td>7.14519</td>\n",
       "      <td>157174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20231203</td>\n",
       "      <td>7.12263</td>\n",
       "      <td>7.14628</td>\n",
       "      <td>7.15483</td>\n",
       "      <td>7.12231</td>\n",
       "      <td>7.13279</td>\n",
       "      <td>7.15292</td>\n",
       "      <td>7.15553</td>\n",
       "      <td>7.12514</td>\n",
       "      <td>483522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20231202</td>\n",
       "      <td>7.12214</td>\n",
       "      <td>7.12263</td>\n",
       "      <td>7.12311</td>\n",
       "      <td>7.12214</td>\n",
       "      <td>7.12595</td>\n",
       "      <td>7.13279</td>\n",
       "      <td>7.13340</td>\n",
       "      <td>7.12531</td>\n",
       "      <td>418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20231130</td>\n",
       "      <td>7.13987</td>\n",
       "      <td>7.12214</td>\n",
       "      <td>7.15549</td>\n",
       "      <td>7.12174</td>\n",
       "      <td>7.14933</td>\n",
       "      <td>7.12595</td>\n",
       "      <td>7.15621</td>\n",
       "      <td>7.12393</td>\n",
       "      <td>301089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20231129</td>\n",
       "      <td>7.14162</td>\n",
       "      <td>7.13987</td>\n",
       "      <td>7.15698</td>\n",
       "      <td>7.12247</td>\n",
       "      <td>7.14464</td>\n",
       "      <td>7.14933</td>\n",
       "      <td>7.15768</td>\n",
       "      <td>7.12315</td>\n",
       "      <td>522710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3554</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20120223</td>\n",
       "      <td>6.29600</td>\n",
       "      <td>6.29660</td>\n",
       "      <td>6.30110</td>\n",
       "      <td>6.29450</td>\n",
       "      <td>6.30090</td>\n",
       "      <td>6.29970</td>\n",
       "      <td>6.30310</td>\n",
       "      <td>6.29660</td>\n",
       "      <td>9202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20120222</td>\n",
       "      <td>6.29640</td>\n",
       "      <td>6.29600</td>\n",
       "      <td>6.30190</td>\n",
       "      <td>6.29320</td>\n",
       "      <td>6.30130</td>\n",
       "      <td>6.30090</td>\n",
       "      <td>6.30360</td>\n",
       "      <td>6.29630</td>\n",
       "      <td>9891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3556</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20120221</td>\n",
       "      <td>6.29180</td>\n",
       "      <td>6.29640</td>\n",
       "      <td>6.30090</td>\n",
       "      <td>6.28980</td>\n",
       "      <td>6.29690</td>\n",
       "      <td>6.30130</td>\n",
       "      <td>6.30410</td>\n",
       "      <td>6.29500</td>\n",
       "      <td>11092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3557</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20120220</td>\n",
       "      <td>6.29990</td>\n",
       "      <td>6.29180</td>\n",
       "      <td>6.29990</td>\n",
       "      <td>6.28410</td>\n",
       "      <td>6.30210</td>\n",
       "      <td>6.29690</td>\n",
       "      <td>6.30210</td>\n",
       "      <td>6.29080</td>\n",
       "      <td>6605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3558</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>20120218</td>\n",
       "      <td>6.29990</td>\n",
       "      <td>6.29990</td>\n",
       "      <td>6.29990</td>\n",
       "      <td>6.29990</td>\n",
       "      <td>6.30210</td>\n",
       "      <td>6.30210</td>\n",
       "      <td>6.30210</td>\n",
       "      <td>6.30210</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3559 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ts_code trade_date  bid_open  bid_close  bid_high  bid_low  \\\n",
       "0     USDCNH.FXCM   20231204   7.14628    7.15025   7.15353  7.14412   \n",
       "1     USDCNH.FXCM   20231203   7.12263    7.14628   7.15483  7.12231   \n",
       "2     USDCNH.FXCM   20231202   7.12214    7.12263   7.12311  7.12214   \n",
       "3     USDCNH.FXCM   20231130   7.13987    7.12214   7.15549  7.12174   \n",
       "4     USDCNH.FXCM   20231129   7.14162    7.13987   7.15698  7.12247   \n",
       "...           ...        ...       ...        ...       ...      ...   \n",
       "3554  USDCNH.FXCM   20120223   6.29600    6.29660   6.30110  6.29450   \n",
       "3555  USDCNH.FXCM   20120222   6.29640    6.29600   6.30190  6.29320   \n",
       "3556  USDCNH.FXCM   20120221   6.29180    6.29640   6.30090  6.28980   \n",
       "3557  USDCNH.FXCM   20120220   6.29990    6.29180   6.29990  6.28410   \n",
       "3558  USDCNH.FXCM   20120218   6.29990    6.29990   6.29990  6.29990   \n",
       "\n",
       "      ask_open  ask_close  ask_high  ask_low  tick_qty  \n",
       "0      7.15292    7.15097   7.15430  7.14519    157174  \n",
       "1      7.13279    7.15292   7.15553  7.12514    483522  \n",
       "2      7.12595    7.13279   7.13340  7.12531       418  \n",
       "3      7.14933    7.12595   7.15621  7.12393    301089  \n",
       "4      7.14464    7.14933   7.15768  7.12315    522710  \n",
       "...        ...        ...       ...      ...       ...  \n",
       "3554   6.30090    6.29970   6.30310  6.29660      9202  \n",
       "3555   6.30130    6.30090   6.30360  6.29630      9891  \n",
       "3556   6.29690    6.30130   6.30410  6.29500     11092  \n",
       "3557   6.30210    6.29690   6.30210  6.29080      6605  \n",
       "3558   6.30210    6.30210   6.30210  6.30210         0  \n",
       "\n",
       "[3559 rows x 11 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd_fx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "089826a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_qty</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-02-18</th>\n",
       "      <td>6.301000</td>\n",
       "      <td>6.301000</td>\n",
       "      <td>6.301000</td>\n",
       "      <td>6.301000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-20</th>\n",
       "      <td>6.301000</td>\n",
       "      <td>6.301000</td>\n",
       "      <td>6.287450</td>\n",
       "      <td>6.294350</td>\n",
       "      <td>6605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-21</th>\n",
       "      <td>6.294350</td>\n",
       "      <td>6.302500</td>\n",
       "      <td>6.292400</td>\n",
       "      <td>6.298850</td>\n",
       "      <td>11092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-22</th>\n",
       "      <td>6.298850</td>\n",
       "      <td>6.302750</td>\n",
       "      <td>6.294750</td>\n",
       "      <td>6.298450</td>\n",
       "      <td>9891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-23</th>\n",
       "      <td>6.298450</td>\n",
       "      <td>6.302100</td>\n",
       "      <td>6.295550</td>\n",
       "      <td>6.298150</td>\n",
       "      <td>9202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-29</th>\n",
       "      <td>7.143130</td>\n",
       "      <td>7.157330</td>\n",
       "      <td>7.122810</td>\n",
       "      <td>7.144600</td>\n",
       "      <td>522710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>7.144600</td>\n",
       "      <td>7.155850</td>\n",
       "      <td>7.122835</td>\n",
       "      <td>7.124045</td>\n",
       "      <td>301089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-02</th>\n",
       "      <td>7.124045</td>\n",
       "      <td>7.128255</td>\n",
       "      <td>7.123725</td>\n",
       "      <td>7.127710</td>\n",
       "      <td>418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-03</th>\n",
       "      <td>7.127710</td>\n",
       "      <td>7.155180</td>\n",
       "      <td>7.123725</td>\n",
       "      <td>7.149600</td>\n",
       "      <td>483522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-04</th>\n",
       "      <td>7.149600</td>\n",
       "      <td>7.153915</td>\n",
       "      <td>7.144655</td>\n",
       "      <td>7.150610</td>\n",
       "      <td>157174</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3559 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                open      high       low     close  tick_qty\n",
       "trade_date                                                  \n",
       "2012-02-18  6.301000  6.301000  6.301000  6.301000         0\n",
       "2012-02-20  6.301000  6.301000  6.287450  6.294350      6605\n",
       "2012-02-21  6.294350  6.302500  6.292400  6.298850     11092\n",
       "2012-02-22  6.298850  6.302750  6.294750  6.298450      9891\n",
       "2012-02-23  6.298450  6.302100  6.295550  6.298150      9202\n",
       "...              ...       ...       ...       ...       ...\n",
       "2023-11-29  7.143130  7.157330  7.122810  7.144600    522710\n",
       "2023-11-30  7.144600  7.155850  7.122835  7.124045    301089\n",
       "2023-12-02  7.124045  7.128255  7.123725  7.127710       418\n",
       "2023-12-03  7.127710  7.155180  7.123725  7.149600    483522\n",
       "2023-12-04  7.149600  7.153915  7.144655  7.150610    157174\n",
       "\n",
       "[3559 rows x 5 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "code = 'USDCNH.FXCM'\n",
    "dd_fx = pro.fx_daily(ts_code=code)\n",
    "dd_fx.index = pd.to_datetime(dd_fx['trade_date'])\n",
    "dd_fx['open'] = (dd_fx['ask_open'] + dd_fx['bid_open'])/2\n",
    "dd_fx['high'] = (dd_fx['ask_high'] + dd_fx['bid_high'])/2\n",
    "dd_fx['low'] = (dd_fx['ask_low'] + dd_fx['bid_low'])/2\n",
    "dd_fx['close'] = (dd_fx['ask_close'] + dd_fx['bid_close'])/2\n",
    "dd_fx = dd_fx[['open','high','low','close','tick_qty']]\n",
    "dd_fx = dd_fx.sort_index()\n",
    "dd_fx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c4e707c",
   "metadata": {},
   "outputs": [],
   "source": [
    "dd_fx['cl']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cd50f4f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e0a282a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f0fee75b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>name</th>\n",
       "      <th>classify</th>\n",
       "      <th>exchange</th>\n",
       "      <th>min_unit</th>\n",
       "      <th>max_unit</th>\n",
       "      <th>pip</th>\n",
       "      <th>pip_cost</th>\n",
       "      <th>traget_spread</th>\n",
       "      <th>min_stop_distance</th>\n",
       "      <th>trading_hours</th>\n",
       "      <th>break_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>铜</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NGAS.FXCM</td>\n",
       "      <td>天然气</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SOYF.FXCM</td>\n",
       "      <td>大豆</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Daily 00.00 - 18.20</td>\n",
       "      <td>Daily 12.45 - 13.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UKOil.FXCM</td>\n",
       "      <td>英国原油</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Mon 00.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 00.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USOil.FXCM</td>\n",
       "      <td>美国原油</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>XAGUSD.FXCM</td>\n",
       "      <td>白银美元</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>50.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.50</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>XAUUSD.FXCM</td>\n",
       "      <td>黄金美元</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.01</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>WHEATF.FXCM</td>\n",
       "      <td>小麦</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Daily 00.00 - 18.20</td>\n",
       "      <td>Daily 12.45 - 13.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CORNF.FXCM</td>\n",
       "      <td>玉米</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Daily 00.00 - 18.20</td>\n",
       "      <td>Daily 12.45 - 13.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code  name   classify exchange  min_unit  max_unit   pip  pip_cost  \\\n",
       "0  Copper.FXCM     铜  COMMODITY     FXCM       1.0     500.0  None      0.10   \n",
       "1    NGAS.FXCM   天然气  COMMODITY     FXCM       1.0     100.0  None      0.10   \n",
       "2    SOYF.FXCM    大豆  COMMODITY     FXCM       1.0    2000.0  None      0.10   \n",
       "3   UKOil.FXCM  英国原油  COMMODITY     FXCM       1.0    5000.0  None      0.10   \n",
       "4   USOil.FXCM  美国原油  COMMODITY     FXCM       1.0    5000.0  None      0.10   \n",
       "5  XAGUSD.FXCM  白银美元  COMMODITY     FXCM      50.0  200000.0  None      0.50   \n",
       "6  XAUUSD.FXCM  黄金美元  COMMODITY     FXCM       1.0   10000.0  None      0.01   \n",
       "7  WHEATF.FXCM    小麦  COMMODITY     FXCM       1.0    2000.0  None      0.10   \n",
       "8   CORNF.FXCM    玉米  COMMODITY     FXCM       1.0    2000.0  None      0.10   \n",
       "\n",
       "   traget_spread  min_stop_distance          trading_hours  \\\n",
       "0            3.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "1           10.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "2            7.5                0.0    Daily 00.00 - 18.20   \n",
       "3            5.0                0.0  Mon 00.00 - Fri 20.45   \n",
       "4            5.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "5            4.5                0.0  Sun 22.00 - Fri 20.45   \n",
       "6           40.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "7            7.5                0.0    Daily 00.00 - 18.20   \n",
       "8            7.5                2.0    Daily 00.00 - 18.20   \n",
       "\n",
       "                     break_time  \n",
       "0  Daily from 21.00 until 22.00  \n",
       "1  Daily from 21.00 until 22.00  \n",
       "2           Daily 12.45 - 13.30  \n",
       "3  Daily from 21.00 until 00.00  \n",
       "4  Daily from 21.00 until 22.00  \n",
       "5  Daily from 21.00 until 22.00  \n",
       "6  Daily from 21.00 until 22.00  \n",
       "7           Daily 12.45 - 13.30  \n",
       "8           Daily 12.45 - 13.30  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pro.fx_obasic(classify='COMMODITY')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "120d39fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>name</th>\n",
       "      <th>classify</th>\n",
       "      <th>exchange</th>\n",
       "      <th>min_unit</th>\n",
       "      <th>max_unit</th>\n",
       "      <th>pip</th>\n",
       "      <th>pip_cost</th>\n",
       "      <th>traget_spread</th>\n",
       "      <th>min_stop_distance</th>\n",
       "      <th>trading_hours</th>\n",
       "      <th>break_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AUDCAD.FXCM</td>\n",
       "      <td>澳元加元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AUDCHF.FXCM</td>\n",
       "      <td>澳元瑞士法郎</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AUDJPY.FXCM</td>\n",
       "      <td>澳元日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AUDNZD.FXCM</td>\n",
       "      <td>澳元新西兰元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AUDUSD.FXCM</td>\n",
       "      <td>澳元美元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CADCHF.FXCM</td>\n",
       "      <td>加元瑞士法郎</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CADJPY.FXCM</td>\n",
       "      <td>加元日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CHFJPY.FXCM</td>\n",
       "      <td>瑞郎日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>EURAUD.FXCM</td>\n",
       "      <td>欧元澳元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>EURCAD.FXCM</td>\n",
       "      <td>欧元加元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>EURCHF.FXCM</td>\n",
       "      <td>欧元瑞士法郎</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>EURGBP.FXCM</td>\n",
       "      <td>欧元英镑</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>EURJPY.FXCM</td>\n",
       "      <td>欧元日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>EURNOK.FXCM</td>\n",
       "      <td>欧元挪威克朗</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>EURNZD.FXCM</td>\n",
       "      <td>欧元新西兰元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>EURSEK.FXCM</td>\n",
       "      <td>欧元瑞典克朗</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>EURTRY.FXCM</td>\n",
       "      <td>欧元兑土耳其里拉</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>EURUSD.FXCM</td>\n",
       "      <td>欧元美元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>GBPAUD.FXCM</td>\n",
       "      <td>英镑澳元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>GBPCAD.FXCM</td>\n",
       "      <td>英镑加元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>GBPCHF.FXCM</td>\n",
       "      <td>英镑瑞士法郎</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GBPJPY.FXCM</td>\n",
       "      <td>英镑日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>GBPNZD.FXCM</td>\n",
       "      <td>英镑新西兰元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>GBPUSD.FXCM</td>\n",
       "      <td>英镑美元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NZDCAD.FXCM</td>\n",
       "      <td>新西兰元加元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NZDCHF.FXCM</td>\n",
       "      <td>新西兰元瑞郎</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NZDJPY.FXCM</td>\n",
       "      <td>新西兰元日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>NZDUSD.FXCM</td>\n",
       "      <td>新西兰元美元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>TRYJPY.FXCM</td>\n",
       "      <td>土耳其里拉日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>USDCAD.FXCM</td>\n",
       "      <td>美元加元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>USDCHF.FXCM</td>\n",
       "      <td>美元瑞郎</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>USDCNH.FXCM</td>\n",
       "      <td>美元人民币</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>USDHKD.FXCM</td>\n",
       "      <td>美元港元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>USDJPY.FXCM</td>\n",
       "      <td>美元日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>USDMXN.FXCM</td>\n",
       "      <td>美元墨西哥比索</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>USDNOK.FXCM</td>\n",
       "      <td>美元挪威克朗</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>USDSEK.FXCM</td>\n",
       "      <td>美元瑞典克朗</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>USDTRY.FXCM</td>\n",
       "      <td>美元土耳其里拉</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>USDZAR.FXCM</td>\n",
       "      <td>美元南非兰特</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>ZARJPY.FXCM</td>\n",
       "      <td>南非兰特日元</td>\n",
       "      <td>FX</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sun 17.00 - Fri 16.55</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ts_code      name classify exchange  min_unit max_unit      pip  \\\n",
       "0   AUDCAD.FXCM      澳元加元       FX     FXCM       1.0     None  0.00001   \n",
       "1   AUDCHF.FXCM    澳元瑞士法郎       FX     FXCM       1.0     None  0.00001   \n",
       "2   AUDJPY.FXCM      澳元日元       FX     FXCM       1.0     None  0.00001   \n",
       "3   AUDNZD.FXCM    澳元新西兰元       FX     FXCM       1.0     None  0.00001   \n",
       "4   AUDUSD.FXCM      澳元美元       FX     FXCM       1.0     None  0.00001   \n",
       "5   CADCHF.FXCM    加元瑞士法郎       FX     FXCM       1.0     None  0.00001   \n",
       "6   CADJPY.FXCM      加元日元       FX     FXCM       1.0     None  0.00001   \n",
       "7   CHFJPY.FXCM      瑞郎日元       FX     FXCM       1.0     None  0.00001   \n",
       "8   EURAUD.FXCM      欧元澳元       FX     FXCM       1.0     None  0.00001   \n",
       "9   EURCAD.FXCM      欧元加元       FX     FXCM       1.0     None  0.00001   \n",
       "10  EURCHF.FXCM    欧元瑞士法郎       FX     FXCM       1.0     None  0.00001   \n",
       "11  EURGBP.FXCM      欧元英镑       FX     FXCM       1.0     None  0.00001   \n",
       "12  EURJPY.FXCM      欧元日元       FX     FXCM       1.0     None  0.00001   \n",
       "13  EURNOK.FXCM    欧元挪威克朗       FX     FXCM       1.0     None  0.00001   \n",
       "14  EURNZD.FXCM    欧元新西兰元       FX     FXCM       1.0     None  0.00001   \n",
       "15  EURSEK.FXCM    欧元瑞典克朗       FX     FXCM       1.0     None  0.00001   \n",
       "16  EURTRY.FXCM  欧元兑土耳其里拉       FX     FXCM       1.0     None  0.00001   \n",
       "17  EURUSD.FXCM      欧元美元       FX     FXCM       1.0     None  0.00001   \n",
       "18  GBPAUD.FXCM      英镑澳元       FX     FXCM       1.0     None  0.00001   \n",
       "19  GBPCAD.FXCM      英镑加元       FX     FXCM       1.0     None  0.00001   \n",
       "20  GBPCHF.FXCM    英镑瑞士法郎       FX     FXCM       1.0     None  0.00001   \n",
       "21  GBPJPY.FXCM      英镑日元       FX     FXCM       1.0     None  0.00001   \n",
       "22  GBPNZD.FXCM    英镑新西兰元       FX     FXCM       1.0     None  0.00001   \n",
       "23  GBPUSD.FXCM      英镑美元       FX     FXCM       1.0     None  0.00001   \n",
       "24  NZDCAD.FXCM    新西兰元加元       FX     FXCM       1.0     None  0.00001   \n",
       "25  NZDCHF.FXCM    新西兰元瑞郎       FX     FXCM       1.0     None  0.00001   \n",
       "26  NZDJPY.FXCM    新西兰元日元       FX     FXCM       1.0     None  0.00001   \n",
       "27  NZDUSD.FXCM    新西兰元美元       FX     FXCM       1.0     None  0.00001   \n",
       "28  TRYJPY.FXCM   土耳其里拉日元       FX     FXCM       1.0     None  0.00001   \n",
       "29  USDCAD.FXCM      美元加元       FX     FXCM       1.0     None  0.00001   \n",
       "30  USDCHF.FXCM      美元瑞郎       FX     FXCM       1.0     None  0.00001   \n",
       "31  USDCNH.FXCM     美元人民币       FX     FXCM       1.0     None  0.00001   \n",
       "32  USDHKD.FXCM      美元港元       FX     FXCM       1.0     None  0.00001   \n",
       "33  USDJPY.FXCM      美元日元       FX     FXCM       1.0     None  0.00001   \n",
       "34  USDMXN.FXCM   美元墨西哥比索       FX     FXCM       1.0     None  0.00001   \n",
       "35  USDNOK.FXCM    美元挪威克朗       FX     FXCM       1.0     None  0.00001   \n",
       "36  USDSEK.FXCM    美元瑞典克朗       FX     FXCM       1.0     None  0.00001   \n",
       "37  USDTRY.FXCM   美元土耳其里拉       FX     FXCM       1.0     None  0.00001   \n",
       "38  USDZAR.FXCM    美元南非兰特       FX     FXCM       1.0     None  0.00001   \n",
       "39  ZARJPY.FXCM    南非兰特日元       FX     FXCM       1.0     None  0.00001   \n",
       "\n",
       "   pip_cost traget_spread min_stop_distance           trading_hours break_time  \n",
       "0      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "1      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "2      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "3      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "4      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "5      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "6      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "7      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "8      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "9      None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "10     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "11     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "12     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "13     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "14     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "15     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "16     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "17     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "18     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "19     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "20     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "21     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "22     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "23     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "24     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "25     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "26     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "27     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "28     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "29     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "30     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "31     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "32     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "33     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "34     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "35     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "36     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "37     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "38     None          None              None   Sun 17.00 - Fri 16.55       None  \n",
       "39     None          None              None   Sun 17.00 - Fri 16.55       None  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pro.fx_obasic(classify='FX')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2775233a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1e4ff3a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "a867206c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2b9f0086d30>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dff['2012-01-01':]['AU'].cumsum().plot()\n",
    "dd_fx['2012-01-01':]['close'].pct_change().cumsum().plot(figsize=(14,6),grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9725115f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "530dc22f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "64b6ceeb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "141c8682",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2b9f1605d60>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xx = dff['AU']\n",
    "xx_ret = xx.resample('M').sum()\n",
    "fx = dd_fx['close'].pct_change().shift(1)\n",
    "xxx = xx.resample('M').sum() - fx.resample('M').sum()\n",
    "ret = ((xxx < 0)*1)*xx.resample('M').sum().shift(-1)\n",
    "ret.cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "ac067f7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.33735095845773483"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(12**0.5)*ret.mean()/ret.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "3330d8d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.36194239619711616"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(12**0.5)*xx_ret.mean()/xx_ret.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "d0d24802",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2b9f10725b0>"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xx.cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "742ed2f1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87e16c14",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "4487868e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2b9f0b9c310>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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r84KxlZWrS7PpcHoj7yFjm9yVxQ7K8+2MBjUHGvrZUpmLxWxiXVk2J9udU57b4wvwl99/lT8caaeu24PdaqJ80qlHqUiS+SJzTqrMX60LJdmN5TkUOmyRZN7vGaEgK/Sx1Bjdn2kQtLV/mLxMa+TjbF6mFbNJcVF1Aa+3DMhgqFh0ZzpdBDVsKp/dCTxrSrLJtVsozRlLssYgqNEaMWZrVRc5IrstBoKaTeEDoTcsy41amf/H02d46VwPX/vDCc50ulhVnI3JNPOUyWQXVzJXSv1AKbVHKXXvDNfdr5S6dX5CS08ubwCrWVEW/iE12h8bluVS6LBFTiEaGB4hLzNcmYerlJkWDp1sd1JTlDXl9otrCsOLMKZWKUIsJKMynm1l/qFrVvHEp6/BPC7JGsn8THgl5rHWQZYXZJKXaZ2wN8rmitzIa/a4fXS7fDxzspMv/s8RHtnfzEMvN7ClMpe2QS8vnetJi345xJHMlVK3A2at9eXAKqXU2hjXXQ0s01r/bp5jTCsu7wg5dis5dgsmBQ29Q+TaLZTn2SnIstHnHmuzGJV5sSM0uj/dkv5Op5eDTf1cv7Fsyn07q0NTwg5Iq0Uski8/dowvP3aME+1OHDZzZMA/Xnarecqe5zVFDnIyLJFj2l5vHmRbeF8UozI3KdgY7s9vDM+eOdXh5OuPn+IX+5v5/P8coSDLyk8+cGnkF0w69MshvhWgu4BHwl8/CVwFnB1/gVLKCnwP+KNS6q1a68cmP4lS6h7gHoAVK1acR8ipzeUNhBK5SZGXaaV/aIQN5bkopShy2HD5AvgDQfqH/OSHk7nJpFiWN/30xCeOdaA1vHFr+ZT7SnPtVBVmcqChnzddMExQj83fFWIh/OFoOz1uPzaLia2VefPSxjCbFDtrCtjf0Eev20frwDB3X1ENhFqKmVYzywsyybSF9lfZEE7Wvz7YwrkuN1968yZKczKoKXKQn2Xjo7tW89c/P8TaJFmOf77iSeYOwNj/sQ+4MMo17wVOAN8EPqmUWqG1/vb4C7TWDwIPAuzcuXPJTnoOVeahf/b8LFsomYcriAJHqK3SMejFOxKMDIACVBc6ePFsNy+c6eaadSVTnvePR9tZV5Ydc5+Ii6sL+f2Rdp480UFVYRbP/83u+f7WhABCP+M9bj/F2Rn0uH1xzy+Px8UrC3n29GmePR2acnjB8lBlrpRic0VupMUCUOiwUZabwWOH27CZTbzjwuXkZY1Nj3zz1nIyrWaujfJ+SkXx9MzdgFHGZcd4zA7gQa11B/ATQDJFDC5vgJyMsQFKIDJtqzCczI2BnYJxyfzvb91EUXYG731o35RzCbtdPvY19EWtyg1vuqCcsrwMtlfl09g7tGDnjwphTBn88q2b+MTuNbzrkvn7JH5JTWgL3Ydeqkcp2FKZF7nvZx+6jC+9edOE641WynUbSickcgh94r1xUxk2S3rMA4nnuzhIqLUCsA1oiHLNOcA4C2on0HjekaUpo80CRNooG8Ij/UYyN0br88f98K0ry+H3n7yK6qIsHp90RNaTJ2K3WAzXbyzjxc9fx19fHxryONUhg6FiYRibX60pzeZzN6+fkHDP19bledgsJk60O1lTkk12xlhzwWYxTTlU2SiU3nZh8u2lMt/iSeaPAncppe4D7gCOK6W+OumaHwC7lVIvAB8D/nV+w0wfxgAojFXmxjFVRjKvD1fm+ZMqCbvVzNbKPE53Tpxutae2l4o8e1y9P+OH+1TH9IsphJgrY1va6igzq85XhsUcOQzCaLFM5y3bKnj7hcvZvb503mNJNjP2zLXWTqXULuBG4JvhVsrrk65xAX+xIBGmmfGV+ZVrihkNahzh6sJoqxiHSuRn2qY8fn1ZDr8/0o7bF4hUJQcb++PeXrQsN4P8LKskczFrHYNePP7AjFu/NvQOUZabEXNL2fN1SU0h++r72F41c8W/qSKXf7tj24LEkWziahZprfu11o+EE7mYo2BQ4/YHyA0n8zt2VvGdd4+NJxtTEY1kXuCYupfF+vBgknHqSdvAMO2DXi6K80BZpRQbluVIm0XM2j//8SR3P7RvxusaejxUFy3c3O3dG0qxmhWXry5asNdIRenR+U8Rbn8ArYm54ZDFbCIv00qHMzSffPwAqMFI5qfDlbVxSspFcRyUa9iwLJfTHa6Yp50LEU2H00tL//CEc2ajaegdYuUCJvOLqgs4+pWbWVM6f7Nk0oEk80VkbLJltFmiMfrmGRYTdqt5yv1VBVlkWs2RNsnBxn4yrWY2zmK59IZlOQz5R2me4U0pxHgD4dXJ++pjLz5z+wL0uH1UF89/v3y8aO+NpU6S+SIyNgiabitQI5lHq8ohNJ1qXVl2ZEnzwcZ+tlflTxnFn46xmEL65mI2+jyhn9/pkrkx+FmzgJW5iE6S+SLqDS/Vj9YLNxhJfPJMlvHWL8vhdIcLjy/AiXYnO+M8jsuwriwbpeDUDNuDCmHQWsdVmUe2pZVkvugkmS8i4/CI5fmxP4IWhhP9dMl8XVkOvR4/9z93jtGg5sI4j+MyZNksrCx28PixdjzjDpgWIha3L0AgqCnJyaCuxxPzBB9jjvlCTEsU05Nkvoha+ocwKViWF3vv5EJH6OTxWG0WGJsr/p/P1nLNuhKuXFM861jufdNGznS6+MTPXiMgW+OKGRgHo9y4KbSRW7T98UeDmudOd4WOeMtYmGmJIjZJ5ouoZWCYslz7tMuH46nMt1bmUZFn5wNXreShu3fOaTnydRvK+Me3buHZ0938fH/zrB8vlhZja+ar1xSTaTXz3OmuKdc88Nw59jf085kb1i12eAJJ5ouqtX94xt0Kx3rmsSvzvKzQKUJfevOmWQ18TvaXl1XjsJkjg1ZCxNIfrsxLcjJ4x0XL+dXBlglHER5pGeDfnz7LW7ZV8Bc7k/P0+nQnyXwRtfQPTzgGK5qi7HAyz4zv8NvzVRTe2U6I6RiDn/lZNr74hg1UF2bxfx55HWd4htZjh9uwmBRffduWuFYii/knyXyRBEaDdDi9VM6QzI3KfLqe+XwqyrZFZtkIEUt/+DjDgiwrjgwL/37ndtoGh3n45QYgdPDJtqp8cqeZdisWliTzRdLp8jEa1FROM5MFQjNVrl1XwiUr41/ReT6KHFKZi5kZbRZjc7gdKwq4oDKPP5/uYsgf4Hibk4tnOUVWzC9J5oukpS80/3amNosjw8LD77+EmuLFmadbnG2j1yOVuZhe/5CfXLtlwhjNtetLOdw8wHOnuwkENTtrFqcAEdFJMl8kreEj32Zqsyy2omwbfR6/7NMiptU/NBI5Ccuwe30JWsO3nj6LUsx6vYOYXzIZdAG5vCN88OEDbK/Kj8y7TbazN4scGYwGNYPDU9+sQhgGhvxTZlhdsDyfgiwrpztdbFiWE2nBiMSQynyB+ANBPvKTg7xa38d/v9zAkZYBirMzkm6DIGP2TK9H+uYitv4hP4WT1j6YTSpyHu1st5QQ80+S+QL51jNnePlcL3993Rr8o0GePtmVdC0WgOLs0IrTHpnRIqbR7xmJOsNq1/pwMp/FFsxiYUibZYG8WtfHxTUFfPam9RxpHeS5090sT7IWC4yrzCWZi2lEa7MAvGFLOd0uH7dsWZaAqMR4UpkvAK01Z7vcrA2f7fm+K1cCM89kSYSi8F4w0mYRsfgDQTz+0chJWOPZrWbuuWZ10rUPlyKpzBdAj9vP4PAIa8JnJV6ztphP7F7Dmy4oT3BkUxVkWVFK2iwitsjqTxkgT2qSzBfAuS43AGtKQ8lcKcXnbl6fyJBisphNFGTZ6JWFQyIGY8FQtMpcJA9ps5yHLqcXd5T9wM91T0zmya7IIUv6RWx9kaX8UpknM0nm5+EvvruHbzx+asrttV1uHDYz5dPsW55MirJt0jMXMY1tsiWVeTKTZD5HfR4/jb1DkZbKeOe63KwpzU6Z3eOKsjOkMhcxjbVZpDJPZpLM5+hUhxOA9sHhKfed63KzOkVaLADFDptstiViaukP7StUKAOgSU2S+RydDp9s3z7oReuxfU2c3hE6nN6U6ZdDaOGQ0xvAH5Dj48REI6NB/ue1Fq5eWyzTD5OcJPM5Mk629wWCkQEiCPXLgci0xFRQFF4F2ie7J4pJnjjWQafTx19dUZPoUMQMZGriHJ3qcGJSENSh6jzDaua+J89wtHUASJ2ZLDC2CrTH7Zv2sGmx9Dz8SgPVRVnsXl+a6FDEDKQyn4PRoOZ0p4uLqkObC7UNDPP86W4eermeTqePmzeXUV20OPuRz4ficDLvdknfXIw51eHkQGM/d11WjcmUGoP5S5lU5nPQ1DeEdyTI7g2l7G/op21gmD6PH5OCJz9zTcr1FlcVhz5FnOl0sXuDVGAixBgXMjbTEslNKvM5ONUemsly5epibGYT7YNeTnW4WFnsSLlEDlDgsFGRZ+dE+PsSAqDT6QWgLFdab6lAkvkcnOxwYVKh8zqX5dlpCyfzDctyEx3anG2qyOVEmyRzMabT6SPTaiY7Qz7ApwJJ5nNwtGWAmmIHmeFVnrVdbpr6hli/LCfRoc3Zpoo8arvdeEdGEx2KSBJdLh9luRkps/htqZNkPksu7wgvn+tl17pQb7kyPzPSnkjpZF6eS1CP9UmF6HR6KZUWS8qQZD5Lz5zswj8a5E0XhDbjL88f+2HfkMLJfHNFqEUkfXNh6Hb5KM3JSHQYIk6SzGfpD0fbWZZrZ0dVaFpieV7owIksm5mqgqxEhnZelhdkkpNhkb75JJ1Ob2TrhqVEa02n0yuDnylEkvksuH0Bnj/TzS1blkXm3VaEK/N1ZTkpPRdXKcXGilypzCf55M8Ocfv9r0RmdiwVbl+AIf+oVOYpRJL5LDxzshN/IMgbt46dGGRU5qncYjFsKs/lZLuTYFDPfPESsL+hj30NfQz5R/nmE6fpGPTywYf38/yZ7kSHtuC6wgvIpDJPHTLnKE5aa/775QaWF2SyM7zyE6CqMIvsDAsX16T+6eRry7IZ8o/S4fRSkYSHTy+2B56rpdBh4y3bKvjhKw28eLabLpePLpePa9el90Ia45OIVOapI67KXCn1A6XUHqXUvTNcV6aUOjQ/oSWXV2p7Odw8wEeuXT2hnZKdYeGVv72O2y+sTGB08yMvM3T4wPjTk7TW3Hjf8/xoT0NigkqQk+1O/nyqi/ddUcPnbl5PaU4GQQ1/edkKjrQMcqRlINEhLihjaweZzZI6ZkzmSqnbAbPW+nJglVJq7TSX/yuQliXdt/98lrLcDN5x0fIp9+XarWkxF9cRXhwyPpn3uP2c7XLz8rmeRIWVEM+dDrVS3nNZNdkZFn73yat46jPX8PlbNpBpNfPTvU1xPY93ZJQ/He+YsE1yKhhb/SmVeaqIpzLfBTwS/vpJ4KpoFymlrgM8QEeM++9RSh1QSh3o7k6tnuPRlkH21vXxoatXpeRy/XgZK/3c3rFk3tDrAeBM59QTldJZrzu0+tE4kKEs106Bw0au3cpbt1fw29fbGBwemfF5/uv5Wj7844M8cSzq2yJpyerP1BNPMncAreGv+4CyyRcopWzAl4AvxnoSrfWDWuudWuudJSWp1W881NwPwK3bKhIcycIy3riecZV5fU8omTf0epbU6tBejz+yNfBkd1xcxfDIaMyB0B/taeBQUz9D/gA/fKUBgPufq02p6lxWf6aeeJK5m7HWSXaMx3wRuF9rnZaNxNouN9kZlrQfDMqO0mZpCCdzrYl63mm6CiXz6P+/t1TkYTWrqHPyvSOjfPm3x3nvQ/v42h9OMjA0wp07qzjaOsiLZ1OnVdXp9FKaI/3yVBJPMj/IWGtlG9AQ5ZobgI8rpZ4Dtiulvj8v0SWJuh4Pq0ocaV+lROuZN/R6sFlCPyZnOpfOUv9et4+iGGde2iwm1pXlRJ2TX9/jQevQp5ufvtrEJSsL+cfbNrMs185/PntuocOeN90uH6XSL08p8STzR4G7lFL3AXcAx5VSXx1/gdb6Gq31Lq31LuCw1vqD8x9q4tR2uVmdQsfAzZUjIzQeMLHNMsSlKwuxmU1Lqm/e6/bHTOYQmpN/om1wSuuktjv0b/Qv79jGxvJc/ubm9WRYzPzVlTW8Wt9HXffYv6HWmqdPdNI6MPVQ8ESS1Z+pacZkrtBUnQ0AAB3GSURBVLV2EhoE3Qvs1lq/rrWOOUUxnNDTxpA/QNugl1XFqXNy0FxlWMzYzCbcvlBvXGtNY6+HNaXZrCpxLJnKXGtNr8cXs80Cob1setz+Kacz1XZ5UAreuLWcxz91dWT9wdt2VKIUPHq4DQgdlPz5Xx/hgz86wNXf+DMf+fHBCZ+IEklWf6amuOaZa637tdaPaK1Ta0h+HtR1h3rGq1PoTM/z4cgwRyrzbpePIf8oK4sdrCvLWTI7Kjq9AUZGdeQ4vWg2VeQBcHxS37y2201lfiaZtomznspy7VyxuohHD7USGA3ysZ++xq8OtvDRXav58LWreeJ4Bw+9VD//38wcGN/TUvg0mk5kOf8M6sIDgKtK0r8yh1Df3KgQjZksNUUO1i/LoXVgOGmqx4XU5/EDxJzNArCxPLR9w+S+eW137Jbcbdsraeob4gMPH+CpE518+dZNfOGWDXzhlg3csLGMH7xUj8s783TH83W4eYCnTnTy/Jlu/IHglPv31fehFGmxqnkpkUmkM6jtcqNUKKEtBdnjkrkxx7ymyBGZlni208WOFQUxH58Oet2h1kmRI3abIcdupbooi+Ntg5HbgkFNXbeHS1cWRX3MLVuWce+jx3j+TDd3X17N+65cGbnvU9ev5dbvvMT/e/wULm+AQDDI127bSsE0ffu5ONPp4rb/fDny95KcDD567Wref9VYLK/W97JhWS55WdZ5fW2xsCSZz6Cux8Pygsy0Xiw0XnaGJdJmqe8ZwmpWVOTbsVoUSsEfj7anfTLvcYcq88IZEmloENSJyztCUId6zcMjozE/xeXYrbzvypW09A9x75s3Tbhv6/I8rttQyk9fbSI7w4I/EORIy0t86507uKh6/v69XwjPjf/xBy7BHwjy4At1/OPvT3DJykK2VObhDwQ52NjPOy9eMW+vKRaHtFkm6XJ66Rgc2+50qcxkMYxvszT2eqgqzMJiNlGel8nbdlTy8J5G2geTa/bFfOv1hCrz4mkGQCGUzBt6h9j6lSe5/t+e43BTaJnFdD8vX3zDBr7z7guxmqe+9f7pti38w1s28/IXruORj1xOMKh5+wOv8NGfHJwy0DpXr9T2UlOUxdVrS7h+Yxnfu3snORkWHni+FoCjrYN4R4JculJaLKlGkvkkH3j4AJ/6RWivsGBQU9/jYVXx0knm2faxZN7cP8SKwrEDNz5zwzrQ8K2nz87puX99sIW9db3zEud8CwY1//KnU5zrctMbZ2V+245K7txZxcd2rabX4+cffnccgNWlc2vJVeZncvcVNeRlWdlelc+Tn72WT9+wlmdOdfH1x0/O6TnHGxkN8mpdL1esKY7clmu38p7Lqnn8aDv1PR721fcBcIkk85QjyXyc0x0ujrYOUhuewdLu9E77sTkdZdvG2iy9bj8l46rTqsIs3nPZCh450ExXjMMa/ni0PeogXjCo+fJjx/jb/z2alPul1/V4+M9na/n5vib6PH5y7ZbIYqlYqgqz+MY7LuDzt2zgzp1VdLl85NgtE/7Nzkd2hoVP37COuy6r5rHDbTT3DZ3X8x1pGcDjH+XK1cUTbn//lTVYzCb+5lev8+ihVtaUZk87LVMkJ0nm4/zvoRYAetw+hvwBGo2ZLEtgjrnBkWHB7Q2E5lq7py5pv3FjGcEYS/sbez187Kev8Y0nTk25r6lvCI9/lPoeDy+cTb6N1oyBzENN/fS4fTO2WCb7PzetJzvDwuqS7HlfKfyhq1dhVor/CrdC5uqVc6FPRZevnjhAW5pr5/M3r6e+x8PpThe70nyv9nQlA6BhwaDmsUNt2K0mvCNBWvqHaegNVULVSyiZZ9stePyjOIcD+EeDU+ZaV4XbLs39U6tEYyrjL/c385FrV3OkZZAXz3bztdu2RqbwWc2KH+1pZNf60gX+TmbHmFt9rM2JSalppyVGU5KTwYPvvYgMy/wPlC/Ls/P2i5bzqwMtFDlsbKrIY3NFLssLMuP6xeHyjnCqw8VTJzvZVJ4btX30watX8YGrVtLn8Uf2tRepRZJ52N66XjqcXj5w1Up+8FI9zX1DNIb3JSlfQsuas8NL+pvCH+knV6jL8uyYFLT0Tx0ENdoAo0HNJ352iKOtg4wGNXddVsOJNidmk+IDV63iuy/U0tDjoSaJfkkeax1EKfAHghxuHuD6jbP/ZXPFpPbFfPrEdWs43jbId549h9GlyrFb2FSey/uuXMktW5bFfOxHfnKQl8NV+cd3r455nVJK2ispTNosYX881o7DZuavrqgBQompodfDisKslD6oebaMzbaMOeaTK1RreGZLtP5tY+8QGRYT77m0msPNA6wNr5p9pbaHk+1OVpc4eP+VNdjMJj71y8NJswBJa82x1kGuWRtqLwSCOumSWmV+Jr/9xFUc/4dbePTjV/K1t23hLdsq6HL5+NQvDnGuK/rq3MBoaKrhrdsq+MNfX8Vnb1y/yJGLxSLJPGxvXR8XryxkeUEmmVYzTX3DNPQMLZnFQgZjG1yjMo+2cGZ5QWbUyrypLzT75bM3ruPTN6zlF/dcxqpiBy+f6+FEu5NN5bmU5tr5zrsv5FjrIPf86EDUFYiLraV/GKc3wI2byiL7kRTP82Kd+ZJpM7O9Kp/3XFrN1962lV9++DKybGY+88vXqe/xcLCxf8LmX2c63XhHgtywsZTNFXmYl1BhstRIMic04Hmuy81lq4pQSlFVmElT3xCNfR5qirJmfoI0YiRzYx/zaPuTVBVmxUzm1UVZFDhsfPqGdeRn2bhyTTGv1PbSPuhlU0UuADduKuMf37qZV2p72TPDVMXJyWk+/cufTvHOB/dwuDk0P3xrZR7bq/IBkq4yj6U0x87Xb9/K0dZBdv/rc7z9gVf40Z7GyP3GWaUXLM9PVIhikUgyB16tC82tNRZKVBVk8VpTP96R4JIa/ISxNktjuDKPNli2vCCTTpcXX2Ds5CGtNU19Q5EBUsOVa4rwhavvTeV5kdtv3BQ6sMr4pRHN0ZZB3v7AK/zp+MLs73agoZ+9dX380+9PYDYp1i/Liaxune0AaCLdsqWcb79rB998xwVcXFPAfzx9Bmd4eujrLQPk2i1LrihZiiSZE9qLwmEzs6UylGyqCrMimy0ttTeBUZk39nooyLJiibJScXlBFlpD28DYXPMet58h/yjVk5L55auKMSZcGJtTAZRkZ5BlM0d689EYW+7uqV2YhUY94T1Yulw+1pZmY7eauWJ1EUrByhT7JX7rtgru2FnFl2/dTP/QCPc/G5rG+HrzINuq8tP+YBUhyRwIzWS5qKYwssR6eUFm5L6l2jPvdMbez7sq/O8zfhDU6LGvmPTLLy/LytbKPMpyMyY8n1KK6iIHjb2xF8I0hhP9vob+OXwnM+tx+3nr9goq8zMjKx63VeVz8N4b2VyRN8Ojk9OWyjzetqOSh16u53jbIKc7XWyTFsuSsOSnJva6fZzpdHPbjsrIbcYS9tAmU5mxHpqWHONOY4+1n/fy8L/P+L55U18o8a4onPrL7+/fvCnqSfY1RVnT7pFuzPM/1eHE6R0h1z5/85/9gSCDwyOsKs7m/91+AVbzWOU60zL+ZPfFN2zgudNd3P3QPkaDmguWp+YvJjE7aV+ZzzR4tj9c9Y3fttTo+1YVZi250f8c+1gyj1WZL8u1YzEpWsYtHGrqHUapiZ9qDDtrCrl+Y9mU22uKHTT3DxEYjT6jpbHXQ3aGBa1DA6HzKbKZVo6NTJs5ajspVZXl2vnG2y+I7P64rUoq86UgfX6Co3j2dBc7v/o0g0OxN/w/3eFCqdAxYAYjmS+1FgtAhsUU+QUWa3qe2RT6xNI8rjJv7POwLNc+q62Ca4qyGBnVtA9G3+eloXeImzaXYTEpDjT0zeK7mFmPK5To5msflWRz0+Zl3HPNKrZV5ctZnktEWrdZTrW76PX4OdI6wNVro+83ca7bPWW/8tAeGw52LMGKRimFw2bG6Q1MOz2vqjBzQmXeHGUmy0yqw78sG8Jb7Y43MORncHiETeW51HZ72F8/v5V5tzv0C6Q4jc+5/Ls3bkx0CGIRpXVlbvRpj7U6Y15zrsvNmij7Tz/x6Wv4+O41CxZbMjMGQafbbGp5fhbNfWOVeUPv0JSZLDOpiSTzqYOgkX1xihxcUlPA4ZaBCVMhz1e6V+Zi6UnzZB56wx4bd7TXeKNBTV23mzVRDmu2mk1Lahn/eNnhvvl0c63XlmXT4/bR5fLSPjhMt8sXWRQUr9KcDOxWU2R3yvGMmSwri7O4qLoQfyA45fDk89Htju8ACiFSRVq3WcYq8+jJvLV/GF8gGDWZL2WOSGUeO5kbi2teaxyIDDLP9jg5k0lRXeiIWpnX93jCA6pZkVksrzX2c+E8HVnX4/bhsJnJtC2N4wBF+kvrZD4QHvhs7B1icHhkytaeZ8ObE0kynyieNsuWylxsZhOvNfWjAJvZNGFRULyqi7IiW+eO19g7REVeaCzDbjVTmZ/JofCy+/nQ4/andb9cLD1p3mYZITM8sHkiykd044CFNSWzT0LpzEjm0w2AZljMbKnM5WBjP4eaBthcmTunvbxrih009g1NOX2ooddD9bgFSDtW5EfO2JwPPa7ZH0AhRDJL62Q+MDQSWdl3PErf/FyXm5KcDPKyZDP+8RwZFjIsJhwztCAuqi7gaOsgR1oH2FE1t/bH6hIH/kAwsheMobF3KDLbBUItnNaBYTqdXr74P0ci523OVeg0odReHCTEeGmdzJ3DI6wqcVCeZ4/aNz/XHX0my1J306Yy3nt59Yz7eVy4ogB/IIh3JMj2FXObxmnsh3N03P+f5r4h+jx+1pWN/b+5MPz8D71Uzy/2N/PDVxo41TH3AdG5HA0nRDJL22QeGA3i8gXIy7SyuSKPI+OSxQ9frufRQ62haYnSL5/ips3L+L9v2jTjdRdWj1Xjc52Tv64sB5vFxNGWsRbK0yc7Adg97mi5TRWhHv13X6ijONtGts3Cvz91Zk6vOTIapH9ohBLpmYs0krYDoE5v6BSb/EwrO1bk8/TJTvo8fkZGg3zldyci10kyn7uyXDuV+Zn4AsGoy/jjYTWb2LgsZ0Jl/udTXawucUw4Vi7DYmZzZS6Hmgb42K41OL0j/MfTZznaMsjWWe490hte5i6VuUgnaZvMB4ZCb9i8LGvko/y++t7I3tpfuGUDJ9udkX21xdx8+NpV+EaC57XF6pbKPH57uI1gUOPxB9hb18v7rlw55brrN5TiHB7h3ZeuYGQ0yMOvNHDvo0f59UeviOx4GY8emWMu0lDaJnNjjnl+po0Lludjt5rYW9eHLzBKjt3CPdesWnKbaC2E915ec97PsbUyj5++2kRj3xAn252MjGqu3zD1QOVPXLeWj+9eg1IKu9XM1962lY/99DW+8+dzfObGdXG/nrFgqCRHBkBF+kjbnrmRzHMzrdgsJi5cUcC++j721PZy6cpCSeRJxGiTHG0d5OkTneRlWrmoOvrsmPGfAN64tZzbd1TynWfPzWowtMcllblIP2mfzPPD0w4vXVnEiXYnDb1DXLaqaLqHikVmDIJ+74U6fnO4lTduLY97S9rP3LiO0aDmtcb456D3SM9cpKG0T+bGqs9LVxVG7rt8tSTzZDJ+EHRndQF//+aZZ9IYjO1djT74z/c1cdO/P48/PDbys1ebIocaG5r6hijIsk44iEOIVJe2ydxYym8k8+1V+dgsJvKzrGxcNrsNocTCe+PWci5dWcj37754Vvul2Cwm8jKtkWR+qKmfM51unjjewdlOF3/3m6M8/ErjhMfU97gnzJQRIh2kbWkyODyCw2aOzHKwW83cvHkZeZmWJbsbYjL78LWr+fC1q+f02OJsG93hPninM/Tfn+xtZGV4BWmXa+LhFw09Q1yxRj6difSStsl8YGjqxlrffteOBEUjFlJxdkakMu9y+VAK9tX38Vr4qDkj0QMM+0fpcHojiV6IdJG2bZbB4RHysmTq2VJQnJMRGdTscnq5ZfMybBYTo1pzxeoiusYl84bwPunSZhHpJq7KXCn1A2AT8Aet9Vej3J8H/AIwAx7gTq21fz4Dna3BYT95mWn7wUOMU5KdQY/Lx8hokF6Pn/XLclhbloPHFyDHbuGV2l78gSA2i4mGHuPQC0nmIr3MWJkrpW4HzFrry4FVSqm1US57D3Cf1vomoAO4ZX7DnL3B4RHyM6UyXwpKcjJw+QK0hA+YLs2x89kb1/GlN2+iNGfibJe6HqnMRXqKp82yC3gk/PWTwFWTL9Ba36+1fir81xKga/I1Sql7lFIHlFIHuru75xhu/KL1zEV6MrayNfasL8sdmz9eGt5My2i1NPR4KMnJiOzZLkS6iCeZO4DW8Nd9QMzNTJRSlwMFWuu9k+/TWj+otd6ptd5ZUlIyp2BnY3B4JLJgSKQ3Y/GPsWe9UY0DlIYTe5czNKOlodcjg58iLcWTzN2AsSVedqzHKKUKgW8D75+f0ObOOzKKLxAkVyrzJcFI5ifaQ5V56YTKPJTYjcq8vmeImuIshEg38STzg4y1VrYBDZMvUErZgF8Bf6u1bpx8/2KbvJRfpDfjLM/jbU5MCoocY2Mlxdk2lAolc5d3hB63T/rlIi3Fk8wfBe5SSt0H3AEcV0pNntHyAeBC4P8qpZ5TSt05z3HOyuTVnyK9Gcm72+WjKDtjwr4uFrOJIoeNbpeXhp7Q0XSrJJmLNDTjKJDW2qmU2gXcCHxTa90BvD7pmgeABxYkwjkwFokUOWQjpaXAbjWTa7fg9AYmDH4aSnLsdDl9nAy3YdaUygHeIv3ENaSvte5nbEZL0qvvcQOwqkQqsKWiOCcDpzcwYfDTUJqTQZfLx6v1fRQ6bKyWnwuRhtJyBWhdj4csmzkyLU2kP2MQNFplHkrmXvY19HJJTeF5nYokRLJKy2Re3+NhZbFD3rRLSEk4mZdEq8xzM+h0+mjuG+aSlYVT7hciHaR1MhdLh7FwKNqnsfGtF0nmIl2lXTL3B4I09w1JMl9ixtos0XvmADl2CxvLZS97kZ6SOpmPBjW/OdTCjfc9z/3PnQOg0+nlnh8doN8TfR+vpr4hglo2UlpqSsIJO2plHu6jX1wjZ7+K9JXUyfwbT5ziM798nfoeD7/c3wzAbw618uSJTg4190d9TL3sirck7d5Qyl9etoIN5VOnHS7LCy1glhaLSGdJncyPtQ6ytTKPL715E429Q9T3ePjzydAeXuMPHBjPmJYoyXxpKcu189XbtpJhmXrkXGV+Jt9/707ee3l1AiITYnEkdTL3+AIUOmzsXl8KhKryA419AHQ5YyVzD4UOG/lyMIUY54ZNZWTZZKdEkb6SOpm7fAGy7RZWFGWxusTBgy/UEtSh+7piVOZ13TKTRQix9CR1Mvf4AmSHq6nd60vxjgQpCq/gi91mkWQuhFh6kjqZu72hyhxCA1zGf8ty7VNOXAdweUfocvkkmQshlpykTebBoMbjH8URPhHm4ppCbt1WwV2XVVOak0G3e2plXtsdmsmytjR7UWMVQohES9oRIY8/AEBOOJnbLCa+/a4dQGhOcZfTh9Z6wpL9s50uANaWya54QoilJWkrc49vFCBSmY9XmmPHFwji8gUm3H6uy43NYqKqIHPKY4QQIp0lbTJ3+0IHTBg98/GM1X6Tpyee7XKzqtgx4XACIYRYCpI267m8E9ss4xlLtifPaDnb5ZIWixBiSUraZD5dmyVSmY+b0TLkD9DSP8yaEhn8FEIsPUmbzCNtlhg9c5hYmdd1e9Aa1pZJMhdCLD1JnMxDlXm0ZJ6bacFmMU1I5me7wjNZZFqiEGIJSt5k7o09AKqUoiQ7Y8KS/rOdbiwmRXWRLBgSQiw9SZvMPX6jZz51FzwI7VE9sTJ3U1PswGZJ2m9JCCEWTNJmPpc3gM1sirqlKRCuzEMDoE29Q+yt65VTZIQQS1bSJnOPLxCzKoexytzjC3DPjw9gUoq/uWn9IkYohBDJI2mX87t9gaj9ckNJtp3+oRG2/cOTBLXm4fdfwoqirEWMUAghkkdyJ/MMa8z737ajkoFhP3armUtXFnL12pJFjE4IIZJL8iZzb4DsadosK4qy+PKtmxcxIiGESF7J2zP3B6LOMRdCCDFV0iZztzcQdSm/EEKIqZI3mfsC5EwzACqEEGJMUidzh5ymLoQQcUnKZD4a1Az5R6edmiiEEGJMUiZz48g4GQAVQoj4JGUyd3slmQshxGwkZTL3hM/2lDaLEELEJymTuXFQs0xNFEKI+CRlMjcq82jnfwohhJgqKZO50TOXylwIIeKTnMncJwOgQggxG3Elc6XUD5RSe5RS957PNfEykrmsABVCiPjMmC2VUrcDZq315Uqph5RSa7XWZ2d7zXhnOl3ceN/zMV+zf8gPSJtFCCHiFU+23AU8Ev76SeAqYHKinvEapdQ9wD0AuRWrWFuWPe2LrinJxmpOyi6QEEIknXiSuQNoDX/dB1w4l2u01g8CDwLs3LlT3/+ei2YdrBBCiOjiKX3dQGb46+wYj4nnGiGEEAsknqR7kFDbBGAb0DDHa4QQQiyQeNosjwIvKqUqgDcA71RKfVVrfe8011w2/6EKIYSIZcbKXGvtJDTAuRfYrbV+fVIij3bN4PyHKoQQIpa45v5prfsZm60y52uEEEIsDBmoFEKINCDJXAgh0oAkcyGESANKa734L6pUN9AY5+XFQM8ChJEHzPdAbSrFCqkVbyrFCqkVbyrFCgsTb6rEWq21Lol6j9Y6qf8ABxboeR9cyrGmWrypFGuqxZtKsS5UvKkUa6w/S7nN8rtEBzALqRQrpFa8qRQrpFa8EusiWrLJXGudMv/zUilWSK14UylWSK14JdbFlQrJ/MFEBzALqRQrpFa8qRQrpFa8qRQrpFa8ixZrQgZAhRBCzK9UqMyFEELMQJK5mEApVaiUulEpVZzoWIRIRwv1HktYMldK5SmlHldKPamU+o1SyhbtHNHJtymlViql/qCUelEp9W9JGG+ZUurFSY+dclsyxqqUKgB+D1wCPKuUij6fNXnitSilmpRSz4X/bE3iWD86Ls7DSqnvLnSs5xnvor/P4ok12jXR4k/WWBfyPZbIyvw9wH1a65uADuCdhM8RBVYppdaqcWeLGrcB3wD+SWt9NbBcKbUrieItAB4mdPISEEmQE25L1liBC4DPaq2/BvyJ6KdKJVu8P9da7wr/OZqssWqtHzDiBF4EvrcIsc45XhLzPpsx1ijX3JKs77FosbKQ77HFmtA+w8T6XxM6O/SN4b+/E3gf8P9Fue0wYAvf9m3grUkUby6hlWTPjbt2ym3JGuu4x1wDvADkJnO8wMeA48A+4AeAJVljHfeYSuCRZP9ZSPT7LFasUa65LFnfY9FiHff3eX+PJbxnrpS6HCgAmpl4jmgZU88WLSP0j/JlpdSthH7TPZMs8WqtnXrSXu7Rblsss401/BgF3An0AyOLFWv4tWcb737gBq31JYAVeGMSx2r4OPDAIoQ4wRziTdj7bIacMOEarfXeZH2PTb5Ga703/PcFeY8lNJkrpQoJ/dZ/P9HPEZ1ym9b6q8DjwAeBh7XW7iSKN2nMNVYd8nHgCPCWhY7TMMd4j2it28NfHwDWLmiQYXP9t1VKmYDdwHMLHOLk1511vIl6n8UT66RrEmausS7UeyyRA6A24FfA32qtG4l+jmiss0UPAyuA+xYp3HjjTQpzjVUp9QWl1HvDf80HBhY4VON15/pv+2Ol1DallBm4DXg9iWMFuBp4VYc/Zy+G84x3Ud9n8cQa5ZqEmGusC/oeS0SPKfyz/FFCHzOeC/+5m9Cb8T7gJKEeWO7k28KP/QfgrmSLd9y1U3p30W5LtlgJfVx8ilAv737Ci8qSON4thKqbo8DXkjnW8N//Gbg9VX5uF/t9FmdOmHzNnbHiT8ZYF/I9llQrQMOj0jcCL2itO2LdliySObbJUilWSK14UylWSK14JdZZvH4yJXMhhBBzk1SDdkIIIeZGkrkQQqQBSeZCCJEGJJkLEaaU2q6U2p7oOISYC0nmQozZHv4jRMqR2SxCAEqprwNvC/+1VWt9fSLjEWK2JJkLEaaU+isArfUPExuJELMnbRYhhEgDksyFGDMMZEFkZzshUoYkcyHGPAXcrpR6mdCmWEKkDOmZCyFEGpDKXAgh0oAkcyGESAOSzIUQIg1IMhdCiDQgyVwIIdKAJHMhhEgD/z+D/zBlZXzj5AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xx.resample('M').sum().shift(-1).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "813665dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_qty</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-09-25</th>\n",
       "      <td>877.850</td>\n",
       "      <td>910.920</td>\n",
       "      <td>867.280</td>\n",
       "      <td>878.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-28</th>\n",
       "      <td>872.350</td>\n",
       "      <td>925.100</td>\n",
       "      <td>867.830</td>\n",
       "      <td>909.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-29</th>\n",
       "      <td>909.450</td>\n",
       "      <td>914.750</td>\n",
       "      <td>860.900</td>\n",
       "      <td>870.95</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-30</th>\n",
       "      <td>870.800</td>\n",
       "      <td>893.690</td>\n",
       "      <td>865.450</td>\n",
       "      <td>870.80</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-01</th>\n",
       "      <td>870.800</td>\n",
       "      <td>876.150</td>\n",
       "      <td>831.550</td>\n",
       "      <td>836.40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-26</th>\n",
       "      <td>2002.105</td>\n",
       "      <td>2018.290</td>\n",
       "      <td>2000.565</td>\n",
       "      <td>2014.15</td>\n",
       "      <td>336362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-27</th>\n",
       "      <td>2014.150</td>\n",
       "      <td>2043.090</td>\n",
       "      <td>2011.555</td>\n",
       "      <td>2041.10</td>\n",
       "      <td>339057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-28</th>\n",
       "      <td>2041.100</td>\n",
       "      <td>2052.050</td>\n",
       "      <td>2035.355</td>\n",
       "      <td>2044.24</td>\n",
       "      <td>435681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-29</th>\n",
       "      <td>2044.240</td>\n",
       "      <td>2047.220</td>\n",
       "      <td>2031.440</td>\n",
       "      <td>2036.29</td>\n",
       "      <td>757614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>2036.290</td>\n",
       "      <td>2075.435</td>\n",
       "      <td>2033.955</td>\n",
       "      <td>2072.04</td>\n",
       "      <td>484644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                open      high       low    close  tick_qty\n",
       "trade_date                                                 \n",
       "2008-09-25   877.850   910.920   867.280   878.75         0\n",
       "2008-09-28   872.350   925.100   867.830   909.50         0\n",
       "2008-09-29   909.450   914.750   860.900   870.95         0\n",
       "2008-09-30   870.800   893.690   865.450   870.80         0\n",
       "2008-10-01   870.800   876.150   831.550   836.40         0\n",
       "...              ...       ...       ...      ...       ...\n",
       "2023-11-26  2002.105  2018.290  2000.565  2014.15    336362\n",
       "2023-11-27  2014.150  2043.090  2011.555  2041.10    339057\n",
       "2023-11-28  2041.100  2052.050  2035.355  2044.24    435681\n",
       "2023-11-29  2044.240  2047.220  2031.440  2036.29    757614\n",
       "2023-11-30  2036.290  2075.435  2033.955  2072.04    484644\n",
       "\n",
       "[4000 rows x 5 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd_fx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c750dc2d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "49c31b96",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "813bf980",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,6))\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax1.plot(dff['2012-01-01':]['AU'].cumsum())\n",
    "ax1.grid()\n",
    "ax2 = ax1.twinx() \n",
    "ax2.plot(dd_fx['2012-01-01':]['close'],'r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "455beb5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_qty</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-08-27</th>\n",
       "      <td>3.95500</td>\n",
       "      <td>3.9550</td>\n",
       "      <td>3.9550</td>\n",
       "      <td>3.9550</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-29</th>\n",
       "      <td>3.95500</td>\n",
       "      <td>4.1140</td>\n",
       "      <td>3.9550</td>\n",
       "      <td>4.0950</td>\n",
       "      <td>751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-30</th>\n",
       "      <td>4.09500</td>\n",
       "      <td>4.1740</td>\n",
       "      <td>4.0890</td>\n",
       "      <td>4.1380</td>\n",
       "      <td>803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-31</th>\n",
       "      <td>4.13800</td>\n",
       "      <td>4.2070</td>\n",
       "      <td>4.1120</td>\n",
       "      <td>4.1850</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-09-01</th>\n",
       "      <td>4.18500</td>\n",
       "      <td>4.1915</td>\n",
       "      <td>4.1105</td>\n",
       "      <td>4.1230</td>\n",
       "      <td>767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-26</th>\n",
       "      <td>3.59300</td>\n",
       "      <td>3.6843</td>\n",
       "      <td>3.5828</td>\n",
       "      <td>3.6718</td>\n",
       "      <td>46553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-29</th>\n",
       "      <td>3.67820</td>\n",
       "      <td>3.7106</td>\n",
       "      <td>3.6579</td>\n",
       "      <td>3.6732</td>\n",
       "      <td>19052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-30</th>\n",
       "      <td>3.67360</td>\n",
       "      <td>3.6943</td>\n",
       "      <td>3.6269</td>\n",
       "      <td>3.6598</td>\n",
       "      <td>44693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-31</th>\n",
       "      <td>3.66165</td>\n",
       "      <td>3.6718</td>\n",
       "      <td>3.6218</td>\n",
       "      <td>3.6660</td>\n",
       "      <td>44913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-01</th>\n",
       "      <td>3.66650</td>\n",
       "      <td>3.7314</td>\n",
       "      <td>3.6447</td>\n",
       "      <td>3.6860</td>\n",
       "      <td>31088</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    high     low   close  tick_qty\n",
       "trade_date                                           \n",
       "2011-08-27  3.95500  3.9550  3.9550  3.9550         0\n",
       "2011-08-29  3.95500  4.1140  3.9550  4.0950       751\n",
       "2011-08-30  4.09500  4.1740  4.0890  4.1380       803\n",
       "2011-08-31  4.13800  4.2070  4.1120  4.1850       232\n",
       "2011-09-01  4.18500  4.1915  4.1105  4.1230       767\n",
       "...             ...     ...     ...     ...       ...\n",
       "2023-05-26  3.59300  3.6843  3.5828  3.6718     46553\n",
       "2023-05-29  3.67820  3.7106  3.6579  3.6732     19052\n",
       "2023-05-30  3.67360  3.6943  3.6269  3.6598     44693\n",
       "2023-05-31  3.66165  3.6718  3.6218  3.6660     44913\n",
       "2023-06-01  3.66650  3.7314  3.6447  3.6860     31088\n",
       "\n",
       "[3100 rows x 5 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd_fx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55dfc92a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2cce2839",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2b9f848f9a0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dd_fx['close'].plot(figsize=(14,6),grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "91ebd553",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>name</th>\n",
       "      <th>classify</th>\n",
       "      <th>exchange</th>\n",
       "      <th>min_unit</th>\n",
       "      <th>max_unit</th>\n",
       "      <th>pip</th>\n",
       "      <th>pip_cost</th>\n",
       "      <th>traget_spread</th>\n",
       "      <th>min_stop_distance</th>\n",
       "      <th>trading_hours</th>\n",
       "      <th>break_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>铜</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NGAS.FXCM</td>\n",
       "      <td>天然气</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SOYF.FXCM</td>\n",
       "      <td>大豆</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Daily 00.00 - 18.20</td>\n",
       "      <td>Daily 12.45 - 13.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UKOil.FXCM</td>\n",
       "      <td>英国原油</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Mon 00.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 00.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USOil.FXCM</td>\n",
       "      <td>美国原油</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>XAGUSD.FXCM</td>\n",
       "      <td>白银美元</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>50.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.50</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>XAUUSD.FXCM</td>\n",
       "      <td>黄金美元</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.01</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sun 22.00 - Fri 20.45</td>\n",
       "      <td>Daily from 21.00 until 22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>WHEATF.FXCM</td>\n",
       "      <td>小麦</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Daily 00.00 - 18.20</td>\n",
       "      <td>Daily 12.45 - 13.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CORNF.FXCM</td>\n",
       "      <td>玉米</td>\n",
       "      <td>COMMODITY</td>\n",
       "      <td>FXCM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.10</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Daily 00.00 - 18.20</td>\n",
       "      <td>Daily 12.45 - 13.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code  name   classify exchange  min_unit  max_unit   pip  pip_cost  \\\n",
       "0  Copper.FXCM     铜  COMMODITY     FXCM       1.0     500.0  None      0.10   \n",
       "1    NGAS.FXCM   天然气  COMMODITY     FXCM       1.0     100.0  None      0.10   \n",
       "2    SOYF.FXCM    大豆  COMMODITY     FXCM       1.0    2000.0  None      0.10   \n",
       "3   UKOil.FXCM  英国原油  COMMODITY     FXCM       1.0    5000.0  None      0.10   \n",
       "4   USOil.FXCM  美国原油  COMMODITY     FXCM       1.0    5000.0  None      0.10   \n",
       "5  XAGUSD.FXCM  白银美元  COMMODITY     FXCM      50.0  200000.0  None      0.50   \n",
       "6  XAUUSD.FXCM  黄金美元  COMMODITY     FXCM       1.0   10000.0  None      0.01   \n",
       "7  WHEATF.FXCM    小麦  COMMODITY     FXCM       1.0    2000.0  None      0.10   \n",
       "8   CORNF.FXCM    玉米  COMMODITY     FXCM       1.0    2000.0  None      0.10   \n",
       "\n",
       "   traget_spread  min_stop_distance          trading_hours  \\\n",
       "0            3.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "1           10.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "2            7.5                0.0    Daily 00.00 - 18.20   \n",
       "3            5.0                0.0  Mon 00.00 - Fri 20.45   \n",
       "4            5.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "5            4.5                0.0  Sun 22.00 - Fri 20.45   \n",
       "6           40.0                0.0  Sun 22.00 - Fri 20.45   \n",
       "7            7.5                0.0    Daily 00.00 - 18.20   \n",
       "8            7.5                2.0    Daily 00.00 - 18.20   \n",
       "\n",
       "                     break_time  \n",
       "0  Daily from 21.00 until 22.00  \n",
       "1  Daily from 21.00 until 22.00  \n",
       "2           Daily 12.45 - 13.30  \n",
       "3  Daily from 21.00 until 00.00  \n",
       "4  Daily from 21.00 until 22.00  \n",
       "5  Daily from 21.00 until 22.00  \n",
       "6  Daily from 21.00 until 22.00  \n",
       "7           Daily 12.45 - 13.30  \n",
       "8           Daily 12.45 - 13.30  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_国外商品 = pro.fx_obasic(classify='COMMODITY')\n",
    "df_国外商品['ts_code']."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc8de6f6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36b7ad1f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "1c663d4e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>bid_open</th>\n",
       "      <th>bid_close</th>\n",
       "      <th>bid_high</th>\n",
       "      <th>bid_low</th>\n",
       "      <th>ask_open</th>\n",
       "      <th>ask_close</th>\n",
       "      <th>ask_high</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20230601</td>\n",
       "      <td>3.6635</td>\n",
       "      <td>3.6839</td>\n",
       "      <td>3.7293</td>\n",
       "      <td>3.6426</td>\n",
       "      <td>3.6695</td>\n",
       "      <td>3.6881</td>\n",
       "      <td>3.7335</td>\n",
       "      <td>3.6468</td>\n",
       "      <td>31088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20230531</td>\n",
       "      <td>3.6586</td>\n",
       "      <td>3.6642</td>\n",
       "      <td>3.6697</td>\n",
       "      <td>3.6197</td>\n",
       "      <td>3.6647</td>\n",
       "      <td>3.6678</td>\n",
       "      <td>3.6739</td>\n",
       "      <td>3.6239</td>\n",
       "      <td>44913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20230530</td>\n",
       "      <td>3.6715</td>\n",
       "      <td>3.6580</td>\n",
       "      <td>3.6922</td>\n",
       "      <td>3.6248</td>\n",
       "      <td>3.6757</td>\n",
       "      <td>3.6616</td>\n",
       "      <td>3.6964</td>\n",
       "      <td>3.6290</td>\n",
       "      <td>44693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20230529</td>\n",
       "      <td>3.6761</td>\n",
       "      <td>3.6711</td>\n",
       "      <td>3.7085</td>\n",
       "      <td>3.6558</td>\n",
       "      <td>3.6803</td>\n",
       "      <td>3.6753</td>\n",
       "      <td>3.7127</td>\n",
       "      <td>3.6600</td>\n",
       "      <td>19052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20230526</td>\n",
       "      <td>3.5909</td>\n",
       "      <td>3.6697</td>\n",
       "      <td>3.6822</td>\n",
       "      <td>3.5807</td>\n",
       "      <td>3.5951</td>\n",
       "      <td>3.6739</td>\n",
       "      <td>3.6864</td>\n",
       "      <td>3.5849</td>\n",
       "      <td>46553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3095</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20110901</td>\n",
       "      <td>4.1700</td>\n",
       "      <td>4.1210</td>\n",
       "      <td>4.1830</td>\n",
       "      <td>4.1090</td>\n",
       "      <td>4.2000</td>\n",
       "      <td>4.1250</td>\n",
       "      <td>4.2000</td>\n",
       "      <td>4.1120</td>\n",
       "      <td>767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3096</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20110831</td>\n",
       "      <td>4.1350</td>\n",
       "      <td>4.1700</td>\n",
       "      <td>4.2000</td>\n",
       "      <td>4.1030</td>\n",
       "      <td>4.1410</td>\n",
       "      <td>4.2000</td>\n",
       "      <td>4.2140</td>\n",
       "      <td>4.1210</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3097</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20110830</td>\n",
       "      <td>4.0920</td>\n",
       "      <td>4.1350</td>\n",
       "      <td>4.1730</td>\n",
       "      <td>4.0810</td>\n",
       "      <td>4.0980</td>\n",
       "      <td>4.1410</td>\n",
       "      <td>4.1750</td>\n",
       "      <td>4.0970</td>\n",
       "      <td>803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3098</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20110829</td>\n",
       "      <td>3.9540</td>\n",
       "      <td>4.0920</td>\n",
       "      <td>4.1130</td>\n",
       "      <td>3.9540</td>\n",
       "      <td>3.9560</td>\n",
       "      <td>4.0980</td>\n",
       "      <td>4.1150</td>\n",
       "      <td>3.9560</td>\n",
       "      <td>751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3099</th>\n",
       "      <td>Copper.FXCM</td>\n",
       "      <td>20110827</td>\n",
       "      <td>3.9540</td>\n",
       "      <td>3.9540</td>\n",
       "      <td>3.9540</td>\n",
       "      <td>3.9540</td>\n",
       "      <td>3.9560</td>\n",
       "      <td>3.9560</td>\n",
       "      <td>3.9560</td>\n",
       "      <td>3.9560</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3100 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ts_code trade_date  bid_open  bid_close  bid_high  bid_low  \\\n",
       "0     Copper.FXCM   20230601    3.6635     3.6839    3.7293   3.6426   \n",
       "1     Copper.FXCM   20230531    3.6586     3.6642    3.6697   3.6197   \n",
       "2     Copper.FXCM   20230530    3.6715     3.6580    3.6922   3.6248   \n",
       "3     Copper.FXCM   20230529    3.6761     3.6711    3.7085   3.6558   \n",
       "4     Copper.FXCM   20230526    3.5909     3.6697    3.6822   3.5807   \n",
       "...           ...        ...       ...        ...       ...      ...   \n",
       "3095  Copper.FXCM   20110901    4.1700     4.1210    4.1830   4.1090   \n",
       "3096  Copper.FXCM   20110831    4.1350     4.1700    4.2000   4.1030   \n",
       "3097  Copper.FXCM   20110830    4.0920     4.1350    4.1730   4.0810   \n",
       "3098  Copper.FXCM   20110829    3.9540     4.0920    4.1130   3.9540   \n",
       "3099  Copper.FXCM   20110827    3.9540     3.9540    3.9540   3.9540   \n",
       "\n",
       "      ask_open  ask_close  ask_high  ask_low  tick_qty  \n",
       "0       3.6695     3.6881    3.7335   3.6468     31088  \n",
       "1       3.6647     3.6678    3.6739   3.6239     44913  \n",
       "2       3.6757     3.6616    3.6964   3.6290     44693  \n",
       "3       3.6803     3.6753    3.7127   3.6600     19052  \n",
       "4       3.5951     3.6739    3.6864   3.5849     46553  \n",
       "...        ...        ...       ...      ...       ...  \n",
       "3095    4.2000     4.1250    4.2000   4.1120       767  \n",
       "3096    4.1410     4.2000    4.2140   4.1210       232  \n",
       "3097    4.0980     4.1410    4.1750   4.0970       803  \n",
       "3098    3.9560     4.0980    4.1150   3.9560       751  \n",
       "3099    3.9560     3.9560    3.9560   3.9560         0  \n",
       "\n",
       "[3100 rows x 11 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd_fx = pro.fx_daily(ts_code='Copper.FXCM')\n",
    "dd_fx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17becd65",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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